AD-A131 163 MODERN HF COUNICATIONS(U) ADVISORY GROUP FORAEROSPACE RESEARCH AND DEVELOPMENT NEUILLY-SUR-SEINE(FRANCE) d AARONS ET AL. MAY 83 AGARD-LS-127

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AGARD-LS-127

AGARD LECTURE SERIES No. 127

Modern HF Communications

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AGARD-LS-I _

NORTH ATLANTIC TREATY ORGANIZATION

ADVISORY GROUP FOR AEROSPACE RESEARCH AND DEVELOPMENT

(ORGANISATION DU TRAITE DE L'ATLANTIQUE NORD)

AGARD Lecture Series No.127

MODERN HF COMMUNICATIONS

The material in this publication was assembled to support a Lecture Series under the sponsorshipof the Electromagnetic Wave Propagation Panel and the Consultant and Exchange Programme of

AGARD presented on 30-31 May 1983 in Athens, Greece; on 2-3 June 1983 in Rome, Italy andon 14--15 June 1983 in Fort Monmouth, N.J., USA.

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THE MISSION OF AGARI)

The mission of ACARI) is to bring together the leading personalities of the N ATO nations in the field, ot scienceand technology relating to aerospace for the following purposes

Exchanging of scientific and technical intonnation:

Continuously stimulating advances in the aerospace sciences relesanit to strengthening the commnon defeniceposture,

Improving the co-operation among member nadtions in aerospace research and deselopinent.

Providing scientitic anid technical advice and assistance to the North Atlantic Military (ommnitteeC Inl the fieldof' aerospace researclt and dev elopment:

Rendering scientific and technical assistance, as requested. to other NATO bodies and to member nation-, inconnection with research aind development problems in the aerospace field:

Plros iding assistance to itienober nations for the purpose of increasing their scientific anid technical potential.

Recommending effectise ss ays for time member nations to use their research and des elopment capabilities torthe comtimon benefit of' the N ATO) com11n Unfit s

The highest authiority within A;A RI) is the National D~elegates Board consisting Of officially appointed seniorrepresentatives fromt each member nation. Ithe mission of AGARI) is carried out through the Panels As hicli arecomposed of experts appointed by the Nattoital D~elegate,. the Consultant and I xcange Progranmme and the AerospaceApplications Studies Programme, *The results of AGA RI) %ork are reported to thle mnember nations amid thie NATOAuthorities through the A A RI) series of pu blicat nit of' which this is one.

Participation in A(;ARI) actis tie, is b invitation only and is nornnall% limited to citizens of the NATO nations.

rTe content of tltis publication has been reproduceddirectly from imaterial supplied by .,(;ART) or the authors.

Published M4ay 1983

Copyrighit 0 A(;ARI 1983All Rights Reserved

ISBN 92-835-1450-5

ii

Nitdh pcasdNnig.ev0sIiie

THEME

Lectures Series 127 is concerned with high frequency communications and i'sponsored by the Electromagnetic Wave Propagation Panel of A(;ARD and implemented bythe consultant and exchange programme.

The aim of these lectures will be to survey problems and progress in the field of li:'OMMUNICATIONS. The lectures will cover needs of both the civil and military

communities for high frequency communications. It will discuss concepts of real timechannel evaluation, system design. as well as advances in equipment, in propagation, and incoding and modulation techniques. The lectures are aimed to bring non-specialists in thisfield up to date so that HF COMMUNICATIONS can be considered as a viable technique atthis time. The problems, difficulties and limitations of IF will also be outlined.

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LIST OF SPEAKERS

Lecture Series D~irector: Dr J.AaronsD~epartment ot A*stronomyBoston University7 '5 Commonwealth AvenueBoston. Massachusetts 0221 iUSA

SPEAKERS

Dr M.Damnell Mr L.PetrieDepartment of Electronics Petrie CommunicationsUniversity of York -22 Barran StreetYork. YO 1 5 DO St. Nepean. Ontario K-2J I;4UK CANADA

D~r MP.(,rossi D~r IV.ThraneH arvard Smithsonian (enter l)ivjsion for E lectronics

for Astrophysics Norwegian Defence Research60 G;arden Street FstahlishmtentCamhridge. Massachusetts 021 38 Kieller N-'007USA NORWAY

D~r P.Monsen Mr Q.C.WilsonSignatron Inc. MIitre Corporation12 lartwell Avenue Burlington RoadLexington. Massachusetts 02 173 Bedford. Massachtusetts 0I 1301USA USA

CONTENTS

Page

LIST OF SPEAKERS iv

Reference

HIGH FREQUENCY COMMUNICATION: AN INTRODUCTIONby J.Aarons I

MILITARY SYSTEM REQUIREMENTSby J.Aarons 2

INTRODUCTION: CIVILIAN AND I)IPLOMATIC REQUIREMENTSby L.Petrie 3

HF SYSTEM DESIGN PRINCIPLESby M.Damel 4

PROPAGATION I: STATE OF THE ART OF MODELLING AND PREDICTIONIN HF PROPAGATION

by E.V.Thrane

REAL-TIME CHANNEL EVALUATIONby M.Darnell 6

INTRODUCTION TO CODING FOR HF COMMUNICATIONSby MD.Grossi 7

MODERN HF COMMUNICATIONS, MODULATION AND COI)INGby P.Monsen 8

EQUIPMENT: ANTENNA SYSTEMSby L.E.Petrie

HF EQUIPMENT: RECEIVERS. TRANSMITTERS, SYNTHESIZERS. ANDPERIPHERALS

by Q.C.Wilson 10

PROPAGATION I: PROBLEMS IN HF PROPAGATIONby E.V.Thrane II

HF PROPAGATION MEASUREMENTS FOR REAL-TIME CHANNELEVALUATION (RTCEI SYSTEMS

by M.I).Grossi 12

ADAPTIVE SYSTEMS IN OPERATIONby L.E.Petrie 13

BIBLIOGRAPHY B

HIGH FREQUENCY COiMNICATION: AN INTRODUCTION

Jules AaronsBoston University

Dept. of AstronomyBoston, MA 02215

SUMARY

The aim of this lecture series is to survey problems and progress in the field of HF communication. Theregion of the spectrum used, 3-30 MHz, allows observers of the RF signal energy to detect both ground waveand sky wave. It is a much used part of the spectrum but it is vital to be able to fulls utilize itsunique capabilities.

1.0 INTRODUCTION

It is easy to see why the disillusion with HF communications set in after World War II - at least with theplanners and those interested in technological advances.

The propagation problems for example are numerous. (i) In the prediction area it is possible to developlong range models for fore~asting monthly medians of frequencies to be used for a specific path in aparticular month and phase of the sunspot cycle. From the viewpoint of the user the enormous range ofvalues used to formulate that monthly median curve means that, for example, over a few hours communicationsare not assured. The techniques for developing long term models and those for forecasting short termvariations are very different; they can be said to be different arts. (21 Several propagation problems areand will continue to be destructive. At high latittides polar cap absorption, which at its worst can lastfor days, will wipe out any system of HF communications that relies on transmitting thru the polar capionosphere. Auroral fading and absorption are probably the most difficult problems of HF. Fast fading andselective path absorption wreaks havoc on HF signals. At equatorial latitudes fading produced by F laverirregularities is active in regions between plus and minus 200 from the magnetic equator; it can be a dev-astating effect.

The 1-30 MHz region is only a small portion of the radio spectrum. At times and under certain propagationand operational conditions even 4 kHz seems to be a wide band. The ionospheric characteristics narrow theband used. The extensive use of HF further bounds the medium with signals piled on top of signals.

Finally there is the possibility of jamming with high power and highly directive signals blotting out thecommunications -- and there is the interception problem.

2.0 EVALUATING AND DEALING WITH CHANNEL PROBLEMS

Any new system will encounter many of these problems. Ihe ideal new system tries to address each problemin a creative way. It deals with the auroral problems by knowing the geographical and signal character-istics of fading and absorption during periods of severe effects. The ideal new sysLem provides for pathdiversity, rerouting messages to minimize the effect of atiroral and polar cap absorption. The ideal svs-tem uses coding for corrections and changes transmission characteristics as a function of its analysis ofreal time channel problems.

The words holding together modern HF radio are Real Time Channel Evaluation; the system enyisaged for thefuture for any use is adaptive. The adaptive aspects contemplated include some or all of the following:

a. Frequency band selection - what general frequency range should be tried for a particular path ata particular time.

b. Channel selector - precise frequency to be used after determining levels of interference, noise,occupancy.

c. Path selector - in the case of routing possibilities the real time channel evaluation would alsodetermine the relay paths utilized.

d. Propagation mode selectivity is also of importance with ground and ionosphere paths available.Within the ionosphere there are many modes, i.e. single hop, multiple hop, sporadic E etc.

e. An area deemed of great importance for networks is to control the power level with excess powerutilized only for reducing interference.

I. Antenna nulling is a more recent possibility for selective point to point communications.g. Channel equalization.h. Modulation selection, coding, error correcting and network protocal are methods where adaptive

systems have and will change HF communications.

3.0 THE USERS

The largest consumers of HF systems at the present are governmental units ranging from National Police topostal and communications services within small nations. There are other groups using HF including dataservices and telephone systems. With regard to the latter remote areas in Canada utilize HF within theirtelephone system for comunications. In many of these governmental uses there is difficulty in sitingthat preclude the use of VHF and UHF. The need in almost all these cases is a voice channel with theusers frequently requesting secure comsunications.

I 1-2

In the area of civil aviation there are extensive plans for lF, the need pushed by the investment that wouldbe required for an effective satellite system. There are firm requirements for high performance from an HFdigital data link. "Channels must be available undec many conditions- message and svmaol error states mustbe minimized for full utilization of the data capability. Civil aviation incidentally allows for a tuningof an adaptive system to conditions on individual routes.

The aim of these lectures is to tie together some of the points raised in this introduction. we hope tooutline the problems of HP cotmnunications, the state of the art in coding, equipment. propagation fore-casting. Finally we hope to discuss the research and development efforts necessary to fully exploit HF

communications.

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MILITARY SYSTEM REQUIREMENTS

Jules AaronsBoston University

Dept. of AstronomyBoston, MA 02215

For the military in many nations, if not in all nations, HF turns out to be a primary means of commnica-tions rather than a backup. In some countries no other communications techniques are contemplated forsuch services as ship to shore, aircraft to ground over distances beyond the line of site etc. The vul-nerability of satellites makes us consider HF communications as a primary military communications mediumeven in those nations making use of satellites In their military complex.

The requirements of a military system range from repetitive broadcasts of simple commands on teletype tosecure digital communications. Global operations demand the HF system adapt to propagation conditions inregions varying from equatorial to polar.

In the area of architecture some military needs are as follows:a. Connectiveness: The requirements may range from many users to many users to confining the opera-

tion to a limited group.b. Master station: In almost all cases a master station is contemplated with command headquarters

organizing the distribution of the system. In this case multiple networks are needed to allow communi-cations within limited groups.

c. Relay: Relay may consist of rebroadcasting or rerouting. Path diversity, i.e. moving a signalto a path with minimum propagation outages is an area on which military research and development mustconcentrate.

D. Identification: This is always a difficult area but a requirement in military systems.

The technical requirements from users include many items. While the list may seem to be a wish list, firmneeds can be shown in each of the following areas:

a. Voiceb. Data

g c. Adequate anti-jam margir.d. Securitye. Interoperabilityf. Coverage: ground and skywareg. Channel optimizationh. Message error control

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INTRODUCTION: CIVILIAN AND DIPLOMATIC REQUIREMENTS

byL.E. Petrie

Petrie Telecommunications22 Barran Street

Nepean, Ontario K2J 1G4CANADA

ABSTRACT

HF radio is used extensively to meet civilian and diplomatic communicationrequirements. Briefly described are the non-military requirements for HF commun-ication by exploration companies aeronautical and marine operations, the diplo-matic corp, radio amateurs, as well as by users in remote and isolated areas whereother means of communications are not available.

TYPES OF SERVICES

HF radio provides the following types of services:

Fixed ServiceA service of HF radiocommunications between specified fixed points or locations;External Affairs or the diplomatic corp are major users of this service. An HFservice is provided between embassies and missions in various countries as wellas directly to the home country. The radio facility is usually located in theembassy or mission building with the antennas mounted on the roof. The physicalenvironment restricts types of antennas that can be used on the buildings andthe high RF noise levels in urban areas can seriously degrade the HF service.Antennas should be of a low profile to avoid destruction in case of internalconflict in the country. Telephone operations and private companies are alsomajor users of the fixed service. The HF service is provided to isolated or re-mote areas where more reliable services are not presently available. Generallythe traffic carried is low capacity and limited resources are provided by theuser to improve the system. In many cases small companies use HF to avoid costof long distance telephone charges of the carrier networks. In many mining andexploration operations, 11F radio is used in the initial stages of developmentof their operation because of the length of time it takes to establish A regulartelephone service using microwave relays or land lines.

Mobile ServicesA service of HF communications between mobile and land stations or between mobilestation such as aircraft or ships;The bands available for these services are very congested and the performanceof the systems vary depending on the prioity the user places on the need for re-liable communications. Aeronautical mobile services are required by airlinesproviding regional,national and international flights. For smaller ailine com-panies the radio equipment is inexpensive and performance rather marginal. Forairlines with national and international services the aeronautical land basedstations and equipment is of a high quality and the performance is satifactoryto the user. However, the HF service is not generally used when other more re-liable radio services are available in the area. Many areas of the world havelimited radio services outside the use of the HF band. The mobile service alsoprovides communication between coast stations and ships or between ships. Theground wave mode of propagation enables communication over large distances alongcoastal regions as compared to the use of the higher frequencies. The range forskywave communications varies from a few miles to distances half way around theworld. Depending on the size of the ship and its operation, there is often arequirement for highly reliable communications back to home base.

Amateur ServiceA service ofiself training, intercommunication and technical investigationscarried on by amateurs, that is, by duly authorized persons interested in radiotechniques solely with a personal aim and without pecuniary interest.The portions of the HF band reserved for amateur usage are always congested.Because of the large market for equipment by this group, new techniques areoften tested on and by this group and if successful are later incorporated intocommercial equipment.

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HF SYSTEM4 DESIGN PRINCIPLES

byM.Darnel1

Senior LecturerDepartment of Electronics

University of YorkHeslington

York YOl 5DDUK

SUMMARY

The lecture deals with the general principles of HF communication system design,using as a framework a generalised communication system comprising:

- propagation path- information source and sink- source encoder/decoder- channel encoder/decoder- RF equipment.

The basic properties of the medium relevant to the design, control and operationof H? systems are considered. In particular, the problems of HF system control areexamined in depth.

The lecture is intended to provide a link between the more detailed lecturesconcentrating upon specific aspects of HF system design.

1. INTRODUCTION

In this lecture, the general topic of HF system design will be consider,d 'romthe viewpoints of present practice and future trends. The tw-, major aims of thelecture are:

(i) To examine the fundamental technical problems of HF systemdesign, control and operation together with potentialsolutions;

(ii)To provide an introduction to the more detailed aspects ofHF system design to be examined in later lectures.

The key to the effective use of the HF propagation medium is an appreciation ofits basic strengths and weaknesses so that a system design can exploit the strengthsand minimise the effects of the weaknesses. Above all, a high level of performancerequiresthat care must be taken to employ HF systems operationally for the types oftraffic and service to which they are well matched, and not to impose "unnatural"requirements for which the medium is fundamentally unsuitable.

For convenience, the main strengths and weaknesses of the medium are summarisedin Table I below:

Table 1

Strengths

(a) The ionosphere is a robust propagation medium which recoversrapidly after major perturbations, eg polar cap events(PCE's), sudden ionospheric disturbances (SID's) and highaltitude nuclear bursts.

(b) Long-term (monthly mean) propagation parameters arepredictable with reasonable accuracy.

(c) Each communication link exhibits unique characteristics, egfade rates and depths, multipath structure, noise levels,etc, which potentially can be used to isolate that path fromthe effects of other transmissions in the HF band.

(d) Only simple equipment and operating procedures are necessaryto achieve access to the medium.

(e) Equipment costs are low in comparison with those of othertypes of long-range communications systems.

PI

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Table 1 (continued)

Weaknesses

(a) The ionosphere is subject to sudden unpredictabledisturbances such as the PCE's and SID's mentioned above.

(b) Although the long-term parameters of the propagation pathare relatively predictable, significant departures from suchpredictions can be expected in the short-term (day-to-day).

(c) Levels of manmade interference are high, particularly atnight, and the nature of such interference is inadequatelycharacterised.

(d) A high level of system availability and reliability requiresconsiderable user expertise in manually-controlled systems.

(e) The available capacity of a nominal 3 kHz HF channel islimited to a maximum of a few kbits/s ; data rates of, atmost, a few hundreds of bits/s are more realistic if highlevels of availability and reliability are necessary.

One of the main problems associated with the operation of current HF systems isthat they are employed primarily to pass traffic at a constant rate - even up to 2.4kbits/s and above - in the same way as with line circuits or other less dispersivemedia. However, as will be shown later, the capacity of an HF skywave link isconstantly varying over a wide range which ideally requires adaptation of the signalparameters and/or signal processing procedures in accordance with the availablecapacity at any time. Two factors preventing this form of adaptation at the presenttime are:

(i) The slow reaction time of manually-controlled systems;(ii)The lack of an adequate real-time model for propagation and

manmade interference.

Methods of overcoming these restrictions by improved HF system design are discussed

in this paper.

2. 'iF SYSTEM CCNTROL

The techniques necessary for the effective control of HF communication systemsare essentially the same as those which have already been developed within thediscipline of automatic control. Two communications scenarios which are encounteredin practice are illustrated in Figs. l(a) and 1(b). Fig. l(a) shows a open loopsituation in which there is no feedback path between receiver and transmitter, whilstFig. 1(b) shows a closed loop situation in which such a path does exist. Ideally, theaim of the control procedure should be to make the transmitted signal x(t) and thereceived signal y(t) identical. In both cases, before any form of optimal or sub-optimal control can be applied to achieve the desired purpose of the system, it isnecessary to characterise the propagation path in order to produce an appropriatemodel for use in the control algorithm, ie the path must be "identified".

For the open loop system this can be achieved in two ways:

(i) By using a priori knowledge of the nature of the path, -qfrom previous practical experience and via off-linepropagation analysis programs;

(ii) By multiplexing channel probing signals with the trafficsignals so that the receiver can derive information to modelthe path and hence can adjust its parameters accordingly.

In the closed loop system, the feedback link enables information extracted fromthe transmitted probing signals to be used to characterise the path and then to bepassed back to the transmitter to allow its parameters to be varied adaptively. Theprocess of probing, or identifying, the channel is known as real-time channelevaluation (RTCE) and is discussed in detail in a subsequent lecture (Darnell, 1983).

3. THE GENERALISED COMMUNICATION SYSTEM

Fig. 2 shows the elements of a generalised communication system. To illustratethe functions of the indvidual elements of Fig.2, an example of a digitized speechcommunication system will be considered.

The average information content of human speech is relatively low - comparablewith that of a low-speed teleprinter link (50 - 100 bits/s). However, if PCM isapplied to the speech waveform, typically a digitised rate of 64 kbits/s will benecessary for toll quality speech reproduction. The contrast between the 100 bits'sinformation rate and the 64 kbits/s PCM rate is marked and is due to the fact thatnatural speech reproduction requires the transmission of many more parameters thansimply its information content, eg loudness, pitch, intonation, etc. It is possible

4.,

to di iltis a.'cha rit,, mch es than 64 kbts's and stil to obtain acceptablequality by mplo,-inq a more efficient model of speech production. PCM is a waveform*ncodinq techniqu, whi h i it ises a 4 kHz wide speech bandwidth without regard toany spe-ch 1n-ratio' i-hani sms. Vocoders are systems which achieve lowerdiqitisation rates b mc'i-llinq the mechanisms of speech production more accurately.

3.1 Sourc-- En-oder Leceder

Much of h-' r.,duindan - s I-.ci jeterministic, le its form is predictable;this allows its i -- ,.ntial m. icr or re-moval. A generalised source encoder has thefunction of r-dicinq he r-d. -;in * in an information soorce signal, as shown in Fig.

3. Perfect soer . d Ili A r'sil' in R 2 beina zero and thus I woeld be acompletly unpredictat[. rin&r, Ja-a slram which could not be compressed further.

In practice, efiin s -e.nc-dini 7ik-s R2 '" R l

A spvcifi -. im. -1.. s.,r "- . . nolr for speech is a "formant" vocederanalyser. The frman' m '.:' si--h ipnds upon the fact that a particular speakerwill tend to h3,.. 4 cr - s;o e i I r-uions in which the energy of speech isconcntrated. These hiqh nrr,. r-lions correspond physically to resonances of thevocal tract/cavity and a typical bas-birnI speech spectrum might appear as illustratedin Fig. 4. The vocal tract cavity is therfore modelled in terms of the parameters of4 or 5 resonant circuits. The centre frequencies and response amplitudes of thecircuits will vary within d-fin-d ranges and the values of these parameters aresampled at regular intervals, digitised and formatted, together with digitised valuesof pitch and an indication as to whether the sound at the sampling instant is voicedor unvoiced. The overall data rate required to specify the digitised speech by meansof the parameters of the formant model is normally in the range 1.2 - 2.4 kbits/s,thus representing a considerable reduction in comparison with the 64 kbit/s directlydigitised PCM. Other vocoder models allow a similar reduction in !ate to De achieved.Th,is, some knowledge of the mechanism of speech production enables source encodingprocedures to be developed which can remove much of the redundancy of speech. At thereceiver site, the source decoder employs a formant synthesiser, based upon the samespeech generation model, to which the decoded parameter values are applied toreintroduce the deterministic redundancy and hence reconstitute an estimate of theoriginal source speech waveform. Fig. 5 shows the operation of the source decoderdiagramatically.

3.2 Channel Encoder/Decoder

The function of the channel encoder in Fig. 2 is to add redundancy to thecompressed source encoder output, as shown in Fig. 6. At first sight, the addition ofmore redundancy seems counter-productive since the source encoder has just beenemployed to reduce redundancy in the source signal. However, R3 is now of a formspecifically designed to combat the types of noise and perturbation likely to beencountered during transmission over the propagation path, eg error protection coding- as illustrated in Fig. 7. In the formant vocoder system under consideration, acompressed source rate of 1.2 kbits/s at the output of the vocoder analyser mighttypically be cxpanded to 2.4 kbits/s by the addition of parity check digits, thusallowing various transmission error patterns to be detected and in some casescorrected. A composite diagramatic representation of the processes of source andchannel encoding, showing the relative compression and expansion of data rate at eachstage, is given in Fig. 8. In general, at the receiver site, the channel decodermakes use of the redundancy inserted by the channel encoder in order to correct forthe various types of transmission distortions and produce an estimate of the niodifiedsource signal, as shown in Fig.9. Clearly, the more that is known of the channelbehaviour, the more effective can the channel encoding/decoding procedures be made -hence the requirement for channel identification or RTCE. The nature of the HFchannel will be considered in more detail in the following section of the lecture.

3.3 RF Units

The function of the RF units of the generalised communication system is toprovide the interface between the channel itself and the channel encoder and decoder.For most types of practical system, this interface will involve processes such asfrequency conversion, filtering, amplification, etc. The rale of the RF elements inthe overall HF system design will be discussed later.

4. A SIMPLIFIED HF CHANNEL MODEL

In this section, a qualitative model of the HF skywave channel is described andused as a vehicle on which to base a discussion of the design of HF comunicationsystems.

The problem of maximising the availability and reliability of an HF system isessentially involves the optimisation of a number of system parameters. Theseparameters, which will be classified as "primary" and "secondary", are listed inTable 2 below:

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Table 2

Primary Parameters

(i) Operating frequencies(ii) Transmission start timets) and duration(s)(1ii) Geographical location of the transmitter and receiver

terminals - should this not already be det-rmined by

other considerations

Secondary Parameters

(i) System control strategies(ii) Source encoding/decoding algorithms(iti) Channel encoding/decoding algorithms(iv) Radiated power levels(v) Antenna characteristics

It is seen that optimisation of the primary parameters will dep,-nd for the most partupon the state of the transmission medium at any time, whilst socondary parameteroptimisation will also depend upon many other factors, eg equipment available, typeof traffic required, etc.

The simplified channel model is based upon the primary param, .rs of frequency,time and position/distance, which form the axes of the diagram shown in Fig. 10. Fora given HF system employing a specified set of secondary parameters, the channel canbe considered as giving rise to a set of 3-dimensional transmission "windows" inwhich the signal can be placed in order to yield a specified lv,l of fidelity at thereceiver, eg in terms of say data error rate or speech intelligibility. The fidelityrequirement can also be interpreted as a minimum signal-to-noise ratio (SNR) withinthe windows. Evidently, if the required SNR can be achieved by simple optimisation ofprimary parameters, then less attention need be given to the task of secondaryparameter optimisation.

In Fig. 10, the times tl, t2, ti,etc are the instants at which the windowsbecomeavailable tothesystem user; the valuesof t and the window durations Atarenormally dictated by factors such as fading characteristics, diurnal pathvariability, atmospheric noise, etc. In the frequency dimension, Af represents thefrequency range open for transmission over which the required SNR can be maintained;again, Af is influenced by many factors such as time of day, season and sunspotnumber. id indicates the range of distance or position over which the transmitter andreceiver locations can be varied, whilst again maintaining the specified receivedsignal fidelity criterion. In practice, the available window structure would b.considerably more complex than that shown in Fig. 10: multiple windows in both f andd dimensions could well exist for a given value of t - as illustrated in Fig. II.Also, for the sake of simplicity, regularly-shaped windows are shown in Figs. 10 and11; in reality, the windows would tend to be irregularly-shaped volumes.

As the required SNR is increased, the windows available for transmission willtend to reduceboth innumber andvolume. Adecrease in the required SNR would resultin an increase in window dimensions causing many of the windows to merge togetheruntil, for very low SNR's (eg for manual morse telegraphy), they may well persist formany hours along the t axis. For transmission rates of a few kbits's, the windowdurations may on occasions be only a few seconds, or even milliseconds.

4.1 Effects of Noise and Interference in the Model

The simplified channel model described previously can be extended to incorporatethe effects of natural noise and manmade interference. In the same way as thecommunications transmitter/receiver system gives rise to transmission windows asshown in Fig. 1I, the path from a noise source or interfering transmitter to th.ecommunications receiver will also have associated transmission windows.

The problem for the designer and operator of a communication system is thus tominimise the probability of coincidence between noise/interference and communicationwindows. If partial or complete coincidence does occur, there is a possibility thatthe communications traffic will be disrupted, ie the received SNR will be degraded.Fig. 12 shows a situation where partial coincidence between a communications windowand an interfering signal window occurs, thus effectively reducing the volume of thewindow available to the communicator.

The remainder of this lecture will now be devoted to a discussion of HF systemdesign methods which can

(i) Maximise the size of the communications windowsand

(ii) Minimise the probability of any coincidence betweennoise/interference and communications windows.

These design techniques will be discussed in the context of the primary and secondaryparameters defined previously.

4.4

5. PARAMETER OPTIMISATION AND SYSTEM DESIGN

In the majority of existing HF systems, the extent to which any parameteroptimisation can be carried out is severely limited by the basic system architecture.From the nature of the channel model presented in Section 4, it is obvious that theHF path will have an information carrying capacity which will vary with time over awide range - a characteristic already noted in Section 1. This can be seen byconsidering the classical expression for the maximum error-free transmissioncapacity, C, for a channel having total bandwidth 8 Hz, signal power S and noisepower N:

C = B log2 ( 1 + S/N ) bits/s (U)

All of the three parameters B, S and N as observed at the communications receiverwill be functions of the three primary parameters of frequency, distance and time -assuming a fixed set of secondary parameters. Normally the position of the transmitterand receiver terminals will be determined by logistic or other factors, andtherefore only the frequency and time variability need be considered. An exception tothis simplification is a system employing geographical diversity with a number ofspaced receiving stations where distance is an important parameter to be taken intoaccount; the benefits of this form of diversity will be discussed later in thislecture. If distance variability is neglected, expression (i) can be modified to givethe channel capacity at any instant as:

C =J/log2 1 1 + S(f)/N(f) I df bits/s (2)

Band the total maximum error-free information throughput, I, in a time interval T isthus:

I / dt =/§ 1 o'g 2 [ 1 + S(f,t)/N(f,t) ) d' dt bits (3)

T TBExpression (3) is still approximate in that it represents the information throughputfor a memoryless channel: in practice, HF channels may have memory in the form ofmultipath. However, expression (3) serves to illustrate the potential variability ofthe transmission capacity of an HF channel.

To clarify the concept of the variable capacity channel further, Fig. 13illustrates one possible physical mechanism giving rise to such a variation: themagnitudes of two multipath component modes for the wanted signal are shown asfunctions of time and frequency, together with the amplitude of an unwantedinterfering signal. The fading characteristics of the three signals are assumedindependent in both time and frequency, to the extent that either of the wantedsignal modes or the interfering signal may be dominant. When one wanted signalcomponent has a significantly greater amplitude than either the other wanted signalcomponent or the interfering signal, the possibility exists for relatively highquality, quasi single mode reception - albeit for a short time interval - asindicated by the "window" shown in Fig. 13.

It is interesting at this point to note a degree of similarity between HFchannels and meteor burst paths (Bartholom( and Vogt, i968). Communication usingionised meteor trails can take place only for short periods of time (typically 0.5 -1 s) when a usable trail occurs; the time between the occurrence of such trails isrelatively long - of the order of 30 - 60 S. However, when the path does exist highrate transmission is possible since the propagation is essentially single mode. TheHF propagation model described previously also gives rise to high capacity windows,as shown in Fig. 13, but in contrast to the meteor burst path, having zero capacitybetween windows, the HF path has a residual, lower and variable capacity betweenwindows.

The majority of existing HF systems tend to operate at a constant transmissionrate with fixed bandwidths and signal formats - a situation which clearly forms afundamental mismatch between the techniques employed and the essential nature of thepropagation medium. For a constant transmission rate, R, if the range of availablecapacities is from Cmin to Cmax then, for error-free transmission to be possible

R - Cmin (4)

Thus, for much of any given transmission interval, a constant rate HF system will beoperating at well below its potential capacity. This simple argument leads logicallyto the concept of an adaptive system whose parameters can change in response tochanges in available capacity. However, if constant rate transmission is mandatory,the source and channel encoding procedures must be made adaptive to counter changesin the received SNR. The practical design implications of adaptive operation arediscussed in the following two sections dealing with primary and secondary parameteroptimisation.

44,

5.1 Primary Parameter Optimisation

In order to achieve a certain HF transmission capacity reliably, it is importantto be able to monitor and select appropriate values of the primary parameters offrequency, time and distance/position. In this way, usable transmission windows canbe selected and matched to the type of traffic which it is required to pass. Havingoptimised the process of primary parameter selection, the secondary parameters of thesystem can also be optimised - the topic considered in Section 5.2 of this lecture.

As has been indicated previously, the position and separation of thecommunication system transmitting and receiving terminals will normally be determinedby factors other than the characteristics of the propagation path; thus, the problemof primary parameter optimisation reduces to one of selecting values of frequency andtransmission time for the given path. This selection procedure can be implemented byemploying some form of RTCE (Darnell, 1983). RTCE procedures have been developed forboth the open loop and closed loop scenarios introduced in Section 2. Currently,however, RTCE techniques are only designed to monitor and select thebest of a set ofalternative transmission channels at a specified time; in general, they are not wellmatched to the task of monitoring the short-term time variability of those channels.Thus, in the context of the simplified HF channel model postulated in Section 4,current RTCE algorithms search for transmission windows which are likely to persistfor the complete duration of a fixed constant rate transmission; at the same time,they attempt to minimise the long-term overlap between communication andnoise/interference windows.

In future, since the utilisation of the HF medium will remain at a relativelyhigh level, or even increase, more emphasis must be given to the development of RTCEsystems which enable the available capacity of the medium to be used more effectivelyby monitoring the shorter-term time fluctuations of a set of assigned HF channels.This RTCE data could then be used in the control of an adaptive transmission ratesystem in which the transmission rate at any time could be matched more accurately tothe available capacity. To implement this form of channel monitoring economically, itwould be necessary to time/frequency multiplex RTCE probing signals and measurementperiods with the traffic signals, possibly with the input data stream being bufferedduring the probing/measurement intervals.

One of the main disadvantages of RTCE systems as currently implemented is thatthey are separate from the communication systems which they are designed to support;they require dedicated and expensive units which are comparable in cost to the unitsof the communication system itself. The future trend should be for RTCE to beintegrated into the communication system design and hence to employ the same basic RFand signal processing equipment. Also RTCE in the form of ionospheric sounding, inwhich energy is radiated across a major portion of the HF spectrum, should berestricted to the purposes of ionospheric research and not employed to supportcommunication systems. Rather, integrated communication and RTCE systems operatingonly in assigned channels should be developed. In this way, the spectral pollutionassociated with dedicated RTCE systems would be minimised.

5.2 Secondary Parameter Optimisation

Assuming that RTCE has been employed to optimise the primary parameters of theHF system, design and control techniques for optimising the secondary parameters ofthe system will now be considered by reference to the elements of the generalisedcommunication system introduced in Section 3 and shown in Fig. 2.

(a) System Control Strategies

It should again be emphasised that, in the system control context, RTCErepresents the process of identification, or modelling, which must take place beforeoptimal control can be applied. Clearly, the path parameters are time varying andthus any control algorithm needs to be adaptive in response to such changes. Ifmanual control procedures are used, response times will be at best a few tens ofseconds and there will be no chance of the system being able to utilise relativelyshort duration, high capacity transmission windows (analagous to the meteor burstsituation). RTCE, however, provides the essential information to enable the systemcontrol procedures to be automated - hence potentially providing a greatly improvedresponse time.

The majority of HF systems operate in a closed loop, or 2-way, mode. In additionto RTCE, the control of this type of system requires the ability to be able totransfer information concerning reception conditions between receiver and transmittersites, ie the provision of a high integrity engineering order wire (EOW) facility. Itis a fundamental requirement of such an EOW that it should be capable of passing theessential control data reliably for a short interval after the quality of thereceived traffic has deteriorated to an unacceptably low level due to changes inchannel conditions. The transmission rate required of an EOW normally will beconsiderably lower than that of the traffic channel, thus enabling robust channelencoding (modulation and coding) procedures to be adopted for protection of thesystem control data.

The system control procedures should also allow for:

4--

(i) Continuous checking of traffic quality: an automatic repeatrequest (ARQ) technique would be suitable for this purpose.

(ii) Automatic re-establishment of the circuit should contact belost: probably based upon the use of back-up accurate timeand frequency transmission schedules.

In the case of an open loop configuration with no EOW available, eg a broadcastsystem, the potential for adaptive operation is relatively limited. All adaptationmust be carried out at the receiver in response to RTCE data embedded in thetransmitted signal. Receiver processing techniques such as equalisation, adaptivefiltering, diversity combination of two or more independent versions of thetransmitted signal, antenna null and beam steering, etc are relevant in thissituation.

From the preceding discussion, it is evident that automatic HF system controlrequires the application of considerable information processing power. Therefore,future HF communication systems will inevitably be processor based, with manualintervention only in exceptional circumstances.

(b) Source Encoding/Decoding Algorithms

The function of the source encoder shown in Fig. 2 is to compress or modify thebasic source data, ie to reduce its redundancy. In the case of low rate telegraphydata and analoque speech, the requirement for source encoding is minimal since theseforms of traffic can be transmitted with reasonable fidelity using relatively simplechannel encoding schemes. However, ore of the major technical problems associatedwith HF communication which has yet to be solved satisfactorily is that oftransmitting digitised speech reliably over such a time-variable channel. Existingvocoders typically operate at data rates of between 1.2 and 2.4 kbits/s: at suchrates, reliable HF transmission cannot be guaranteed and,indeed, in spectrallycongested environments such as the Central European region, it is improbable that asatisfactory grade of service can ever be achieved - particularly at night.

Two options present themselves: first, users must accept that secure/digitisedspeech cannot be transmitted reliably over the majority of HF channels - a situationwhich is operationally unacceptable: secondly, more sophisticated speech sourceencoding and system management schemes must be developed to give an averagetransmission rate not exceeding a few hundreds of bits/s. The latter option may notbe achievable in the shorter term without resorting to buffering of the input speechand subsequent transmission at a lower rate over an extended period of time, thusinvolving the system users in significant waiting times until the data has beenpassed.

In general, one of the most effective contributions which the system user canmake to transmission reliability is to minimise the amount of traffic to betransmitted over a given period by the communications system, which is in itself themost fundamental form of source encoding. This then enables greater protection to beapplied to the residual data by more powerful channel encoding procedures.

(c) Channel Encoding/Decoding Algorithms

The channel encoder shown in Fig. 2 is intended to condition the compressed ormodified data from the source encoder so that it can withstand the noise andperturbations likely to be encountered during transmission over the channel. Thechannel encoding/decoding techniques which offer promise of economic and effectiveimplementation with variable capacity HF sytems will now be examined.

Diversity Processing

Diversity processing at HF can potentially provide a significant improvement inthe effective received SNR. Fig. 14 shows the theoretical improvement in the SNR indB for a dual diversity system in comparison with a non-diversity system as afunction of bit error rate (BER) under Rayleigh fading conditions with additiveGaussian white noise (GWN). Clearly,in a practical dual diversity combining system, aperformance improvement of 10 dB in received SNR is achievable.

When the traffic signal is transmitted on more than one frequencysimultaneously, frequency diversity combining can be employed at the receiverproviding that the separation between frequencies is great enough to ensure that thereceived components behave independently in terms of their fading characteristics(Alnatt et al, 1957).

It is well established that, if the receiving antennas are appropriatelyseparated, space diversity can provide one of the most effective ways of enhancing HFsystem performance. If space diversity is not feasible, polarisation diversity can insome situations be used as a somewhat less efficient alternative.

Time diversity (McCarthy, 1975) and the related technique of interleaving(Douglas & Hercus, 1971) have been shown to be effective in combatting burst errorsdue to interference and fading. However, the improvement in performance is onlyachieved at the expense of greater transmission bandwidth and increased processingtime.

If an HF communication system is structured appropriately, qeographicaldiversity in which several versions of the transmitted signal are received at wideliseparated receiving sites can potentially provide one of the most effective countersto propagation fluctuations and interfering signals. The probability of interferir-1signal windows coinciding with communication windows for all links in ageographically dispersed network of the type shown in Fig. 15 is relatively smallcompared with the coincidence probability for any single link in the network.However, combination of the received signals to produce an overall maximum likelihoodestimate of the transmitted signal does require that there are reliableinterconnections between the various sites - a situation which will only apply insophisticated networks where HF is one component of an integrated mix ofcommunications techniques.

Signal Processing Techniques

As has been indicated previously, signal processing in existing HF systems tendsto be relatively simple and based upon the premise of non-adaptive, constant rat,iperation. If variable rate operation is contemplated, a fresh consideration ofpotential signal processing techniques is necessary. Those procedures which appear tooffer promise are now outlined briefly.

Adaptive filtering at the receiver: in which the parameters of baseband or IFreceiver filters are modified to counter changes in the nature of interfering signalsin the communication channel.

Quenched filtering: applied to a synchronous transmission system enables areceiver filter to be opened to receive a wanted signal only over the intervals whernthat signal is expected to be present, as illustrated in Fig. 16. In this way, thefilter is not initialised by noise or interference and the detection decision is madewhen the detector output SNR can be expected to be a maximum. This type of detectionscheme is used in the PICCOLO system (Bayley & Ralphs, 1972). For a given form ofmodulation, if synchronous or coherent detection can be applied, a significantimprovement in system performance can be achieved.

Soft-decision decoding implies that a "hard" detection decision, say I or 0, isaugmented by information concerning the confidence level associated with thatdecision, eg based upon signal amplitude, phase margin, etc. When coupled with errorprotection coding, soft-decision decoding can enhance the performance of a basicdetection system substantially (Chase. 1973).

Possibly one of the most powerful techniques for use in a high interferenceenvironment is that of correlation reception. For this, sets of relatively longsequences with approximately impulsive autocorrelation functions are required so thatmatched filtering can be applied at the receiver. Sequences with suitableautocorrelation properties also allow RTCE data, say in the form of a channel impulseresponse, to be extracted conveniently (Darnell, 1983).

Bearing in mind the variable nature of HF channel capacity discussed previously,it would appear that some form of "embedded" data encoding would be appropriate.Here, several versions of the source data, each keyed at a different rate, would becombined into a single transmitted signal format. At the receiver, data would bedecoded at the highest rate which the channel capacity at that time would allow.System control and re-alignment would be accomplished at intervals by an ARQarrangement operating via the EOW. Fig. 17 shows the principle of this type ofencoding for a transmitted signal comprising three identical data streams, eachclocked at a different rate. At the end of every data block in the slowest stream,the receiver indicates to the transmitter which of the data streams it has been ableto receive successfully in the previous transmission interval; the transmitter thenre-aligns the transmitted data blocks accordingly over the subsequent transmissioninterval. This form of encoding has yet to be developed and implemented for HFapplications.

With the advent of cheap and powerful computing capacity, it is now possible toconsider the introduction of post reception processing a- the receiver. Theunprocessed received signal could be stored, either at a low IF or baseband, and thenprocessed rapidly off-line using different signal processing parameters andalgorithms until a best estimate of the transmitted signal is obtained.

(d) Radiated Power Levels

In the HF band, high radiated power levels are undesirable since they tend tocause spectral pollution and an increase in transmitter and antenna sizes - and hencecosts. The use of RTCE in optisising the primary parameters of an HF communicationsystem will tend to reduce the necessity for higher radiated powers by selectingfrequencies and transmission times for which the received SNR is maximised andinterference avoided. As a general principle, system availability and reliabilityshould be improved by the use of RTCE and more effective signal processing, ratherthan by transmission at higher power levels, the latter should be held in reserve forparticularly vital links.

The RF units of the system should be capable of rapid frequency agility so that

o

full advantage can be taken of automatic and adaptive system control procedures. Theability to change frequency rapidly will also facilitate the RTCE process of findinga channel with an acceptable SNR. This will eliminate the "resistance" of systemoperators to changing frequency except where absolutely essential and thus lead toimproved flexibility and lower radiated power levels.

(e) Antenna Characteristics

Diversity using spaced receiving antennas is an effective method of improving HFsystem performance and should, where possible, be incorporated into a system design.Also, a simple 2-element receiving antenna system can be used to place a null in thedirection of an interfering signal. The depth of the null will depend upon theinstantaneous propagation conditions, but an average depth of a few dB may well beachievable for skywave signals. Against more stable groundwave interfering signals,the nulling procedure will be considerably more efficient.

Again, the systematic use of RTCE and improved system control procedures willtend to reduce dependence upon antenna characteristics.

6. NETWORK AND FREQUENCY PLANNING CONSIDERATIONS

In this lecture, attention has so far been concentrated upon the design ofsingle HF communication systems. However, when a network comprising many such systemsis being considered, other important design criteria should be addressed. A networkwill typically comprise a mixture of groundwave and ionospherically refracted skywavepaths. At the lower end of the frequency band, short-distance paths of the type usedprimarily for tactical communications will employ predominantly groundwavepropagation or mixed skywave and groundwave propagation with consequent interferencebetween groundwave and skywave - particularly at night. Longer distance point-to-point circuits will only employ skywave modes.

6.1 Frequency Sharing and Re-Use

From the viewpoint of spectrum utilisation, it is advantageous to be able to re-use or share frequency assignments between circuits wherever possible, ie to allocatethe same operating frequencies for simultaneous use by two or more independent links.This requires that there is negligible interference between the links. Consideringthe schematic arrangement shown in Fig. 18(a) where two short-distance HF links, AA'and BB', are separated by a long HF path A"B", A" and B" being the mid-points of thetwo short-distance links. Fig. 18(b) shows typical plots of lowest usable frequency(LUF) and maximum usable frequency (MUF) for the three paths. The usable frequencyranges between the LUF and MUF for each of the three paths are shown hatched. If itassumed that the two short-range paths will employ groundwave propagation, then thefrequency chosen can be the same providing that it does not intersect the usableskywave range for the path A"B"; the distance A"B" is too great for any groundwavepropagated interference to occur between AA' and BB'. In Fig. 18(b), two possiblegroundwave frequencies, fGW(L) and fGW(U'' are shown; the lower frequency is chosento be less than the LUF's for the two short-range paths to avoid the possibi lity ofinterference between groundwave and skywave. The upper frequency is chosen to beabove the MUF foL the path A"B" to eliminate skywave interference between the twocircuits. It should be noted that the upper frequency will normally only be usableover very short distances because of the poorer groundwave propagation at higherfrequencies; this poorer propagation is to some extent offset by lower natural noiselevels at higher frequencies.

If the two short-range paths are of such a length and nature that only skywavepropagation is possible, the individual skywave signals using a common frequencyshould again not interfere with each other via path A"B". It is usual, whereverpossible, to operate skywave circuits on a "2-frequency" basis, ie one frequency fornight-time operation and another for day-time. Fig. 18(b) also shows how this type ofoperation can be arranged to fall within the usable ranges for the two short pathsand yet below the LUF for path A"B".

For any given geographical situation involving tactical short-range links separatedby relatively long distances, the above technique may be applicable. This exampleserves only to illustrate the potential value and complexity of HF frequency sharing.If the terminals of the tactical circuits are mobile, their predicted operationalareas must be taken into account in any frequency sharing algorithms, together withany other regions to which it is desirable to restrict propagation. The frequencymanagement of a network of automatic and adaptive HF communication links, each havingintegrated RTCE, will be a significant practical problem. H iever, the spectrumcongestion in the HF band is such that the frequency management of individualnetworks and links must be carried out in a more co-ordinated manner, and must beconsidered at the design stage of any new system.

6.2 Frequency Band Extension

Returning again to the simplified model for HF propagation described in Section4: a similar representation of propagation by the mechanisms of sporadic E-layerrefraction and meteor burst is also valid, with the difference that in these twocases the coincidence probability between communication and interference windows ismuch less. RTCE can also enable the selection of sporadic E modes, which are

4-10

relatively localised phenomena, thus tending to employ frequencies which are somewhathigher on average than for more conventional HF modes. In this situation,interference probabilities will be reduced significantly.

Meteor burst systems have the advantage that the path between communicationstransmitter and receiver is virtually unique with an extremely low interferenceprobability. This type of link, if integrated into the HF system, could be used forEOW purposes. Thus, the concept evolves of an HF type of communication system, withan operating frequency range of say from 2 - 50 MHz, which would make use of anyconvenient propagation mechanism available at the required transmission time.

7. CONCLUSIONS

From this introductory lecture, covering current HF communication system designand future design trends, certain general conclusions can be drawn:

(a) The key to significant improvement in HF system performanceis the effective incorporation and application ofappropriate RTCE techniques;

(b) That the design aim for an HF system should be to achieve--he desired level of performance by the application ofimproved system control and signal generation/processingalgorithms, rather than by the use of traditionaltransmission techniques, high radiated power levels andlarge antennas;

(c) That the variable capacity of the HF path should berecognised and exploited.

Against this background, the major technical problems to be solved in future HFdesigns can be identified as:

- The development of RTCE techniques which can be integratedwith the communications function of the system, employing acommon range of RF and processing equipment;

- The development of automatic system control algorithms andassociated processing equipment;

- The design of adaptive/re-configurable signal generation andprocessing equipment for use in the variable capacityenvironment;

- The provision of highly-reliable EOW facilities for systemcontrol purposes;

- The development of techniques to allow the transmission ofreliable digitised speech over all types of HF paths;

- Evaluation of the benefits of designing HF equipment tocover an extended frequency range above 30 MHz to exploitmore transient propagation mechanisms such as meteor burst;

- Design techniques to minimise system operation and

maintenance costs.

8. REFERENCES

(I) Darnell, M., 1983, "Real-time channel evaluation", AGARDLecture Series 127 "Modern HF communications".

(2) Bartholome, P.J. and Vogt, I.M.,1968,-COMET - A new meteorburst system incorporating ARQ and diversity reception",IEEE Trans. COM-16, 2, 268-278.

(3) Alnatt, J.W., Jones, E.D.J. and Law, H.B., 1957, "Frequencydiversity in the reception of selectively fading binaryfrequency-modulated signals", Proc. IEE, 104, Part 8, 98-110

(4) McCarthy, R.F., 1975, "Error control with time diversitytechniques", Signal, May/June issue.

(5) Douglas, F.W. and Hercus, P.T., 1971, "Development ofAUTOSPEC Mark I", Point-to Point Telecommunications, May.

(6) Bayley, D. and Ralphs, J.D., 1972, "PICCOLO 32-tonetelegraph system in diplomatic communication", Proc. IEE,119(9), 1229-1236.

(7) Chase, D., 1973, "A combined coding and modulation approachfor communication over dispersive channels", IEEE Trans.,

4-1

O CLOSED LOOP OLTPIT

aPEN LOOP )TiU I IN .PT kt

INPUT xl OtT

PROAIA 1NPROPAGA110\ ON

PA11 T H PA TH

FEEDRACK PATH

hUVRl I: BASIC CO,'tINICATION SCENARIOS

IRANS'IITTER SIrE RLCEIUER SITE

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I e DI

SYSTEM CONTROL

FL;LRF . NERAIISES CoISDINICATION SYSTFm

INIORMA ION I NFORMALT ION

RP:DINDANCY SOLURCE REDtUNDANCY

(I + 1 ENCODER R-S URUuMODPIFIED,

SIN AC| COMPRESSEDSOU'RCE S IGNAI.)RN

FIc.!. RE EI NC I ON OF SOURCE FNCODER

I I

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FORMANT FREQUENCIESFIGURE 4: TYPICAL BASEBAND SPEECH

SPECTRUM

MODIFIED/ SOURCE

COMPRED SIGNAL INFORMATION INFORMATIONCOMPRE SSED ESTIM4ATE & &SOURCE SIGNAL . REDUNDANCY REDUNDANCYESTIMATE SOURCE I * R. (I R) (I R.)

( R2 ) DECODER ' ~C ANNL I

(MODIFIED/' ENCODER

COMPRESSED S(TRANSMITTEDSOURCE SIGNAL) SIGNAL)

FIGURE 5; FUNCTION OF SOURCE DECODER FIGURE 6: FUNCTION OF CHANNELENCODER

4-12

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MODIFIED/ MODIFIEDCOMPRESSED r ~ \cOMPRESSEl IM I TYSOURCE SIGNAL ~ ~ RSOURCE SIGNAL. II TDIGITS Dh*1RI)I; ITIS

P ROTVFC T I: o'COD IS, .

FIGURE ;: ER.ROR PROTECTION COIGAS AN EXAMPLE OF CHANNI~L EN.CODIN:.

SOLURCE SOURCE COMPRESSE.D CHANNEL. CHANELIENCOD IN(, MODIFILED f*5c5) ING. FNCODFDPROCESS SOURCE IPROCES'S S 1,..Aa

RATE

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CHANNEL MODIFIED,ENCODED SIGNAL COMPRESSED

ESTIMATE SOURCE Sl I.NAI.

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al CHANNEL ----DFCOIIFR

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I A H

PROPAGATIOIN 1. State of the art of modelling and prediction in HF Propaoation

by F V ThraneNorweojan Defence Research Fstablishment

N-2P17 K jeller, Norway

ARSIRA( T

The lecture reviews the state of the art in HF propaqation modellino and describes the principlesof radio frenuency predictions. As a basis for the discussions, a brief introduction is glien to theionospheric parameters nf importance to HF-propaqat inn. rurrent methods for frequency prediction aresemi-empirical, that is they depend upon a large data hase of ionospheric observations, combined withphysical models of the ionosphere and of radio wave propaoation thrnunh the medium. In addition modelsof the noise and interference environment must he included. The lerture discusses the principles onwhich the methods are based, as well as their limitations. rxamples are liven of the use of Predictionsin system planninq and communications. The relative importance of skvwave and around wave com-munications in the HF-band is discussed.

1. INTRODUCTIIN AND nUTLINF

In spite of the development of satellite communications, microwave links and other rommunicationtechniques, interest in the high frequencv band is still strono. The HF-band (3-30 Ntz' represnts avaluable natural resource and should he exploited as efficientlv as possible. The radio wave" in thisband can travel alonq the earth's surface, bit only for limited distances, dependino in the conduc-tivity of the around or sea. Ffficient reflection of the waves from the innized layers in the uperatmosphere makes lIF radio transmissions over lona distances possible. A prediction of the performanceof a communication cirruit must of necessity be based upon a model of the propaqation medium, as well asof the propagation process itself. The purpose of the present lecture is to review the state of the artof such models, their usefulness and accuracy. First a brief introduction to the most important ori,-ciples of ionospheric radio propaqation will qiv-n. The ionospheric models have been developed fr,,physical principles noverninq the formation of the innosphere and a larqe data base arnuured thrn,many years of measurements. Roth the data base and the models will be discussed.

Furthermore the principle of the prediction techniques will he described, and how these technuesinclude models of the electromaqnetic noise and interference environment. Weaknesses in present predic-tion methods and possibilities for future improvement, will he pointed out, and finally examples of !heuse of predictions in system planning and communications will he siven.

2. A RRIFF INTRODtICTInN Tn InNOSPHFRIP PARAMFTFRS Pf IMOPRTANCF rn HF-PPPAGATION

Ulltraviolet radiation, X-rays and enerqetic particles from the sun and interplanetary spaceinteract with the earth's atmosphere to form the ionospheric layers of free electrons and ions in theheiqht range 5A-500 km above the earth's surface. The free electrons in the eaklv innized innosphericplasma absorb, refract and reflect electromagnetic waves over a wiue frequency canoe. The physics ofradio wave propagation in this medium is now well understood. Propanation can he described by themagneto-ionic theory developed by Appleton and Hartree udden t56fl. In the principle, if the proper-ties of the medium is known precisely, the refractive index of an incident radio wave may be computedand the phase and amplitude of the wave may be found at any point in space. The presence of the earth'smaqnetic field makes the ionosphere birefrinqent, and the spatial and temporal structure of theionospheric layers may he very complex. Therefore, accurate solutions to be the wave equations renuirecomplex and time consuming calculations. Modern hiqh speed computers have made it possible gradually tointroduce more sophisticated and precise raytracinq methods, but in practice the prediction methods arestill based upon simplified models of the propagation process as sell as of the medium. In this sectionsome ionospheric parameters of importance to HF propagation will he introduced.

2.1 Formation of the ionosphere

Figure I shows a typical daytime height distribution N (h) of the ionospheric electron density andindicate how a spectrum of energetic electromaqnetic radiatign from the sun interacts with theatmospheric gases to form the D,-, F- and F-reqions in the undisturbed ionosphere. The fiqure also indi-cates the occasional presence of a thin dense "Sporadic F-layer". The ions and electrons formed by thesolar radiation are lost through recombination, and a simple form of the continuity eouation whichdetermines the ionization balance is:

dN-- q(h X)-affNN (1)

where N im the positive ion density and a is a constant, the effective recombination rate, x is thesolar + nith angle. The height and intenaty of each layer varies in a systematic manner with solarelevation. A first approximation to this variation is shown for a simple model "Chapman" layer inFlqure 2. In the real atmosphere many complex processes may cause deviations from this simple model.

The two ionospheric parameters of prime importance for radio wave propagation are the con-centration N of free electrons and the averaqe frequency v with which an electron collides withneutral molecules and ions. The collision frequency v is proportional to atmospheric pressure. Typicalheight variations of N, v and their product Nav are shown in Fiqure 3.

2.2 Radio wave propagation in the ionosphere

The first principles of hiqh frequency propagation may be understood by considerinq a simple Casein which the earth's curvature and maqnetic field are neqleeted and the ionospheric lavers are horizon-tally stratified. The ray path of a radio wave may then be described by Snell's law of refraction, asshown in fiqure 4, where u is the real part of the refractive index and In is the anqle of incidenceupon the layer labelled n.I. Then

wfsinl0 = 1 sinl = U 2 sinl 2.. . = constant

this means that as the ray travels throuqh the slabs the ray direction rhannes in such a way thatusinl is constant. A continuouslv varyinq medium may be approximated by many thin slabs. If the waveis incident upon the ionosphere from free space so that W a = 1, we have usinl z sin 0. Reflectionnoccurs where I = 900, so that i = sinl. At vertical incidence I = 0 and the reflection conditionbecomes a = 0. Maqneto-ionic theory Lows that, in the simple case we are dealing with, the refractiveindex may he written

/ 2

e

where % is the numher lensitv of free electrons, me the electron mass, f the wave frenuercv and. c 0 thepermittie it, f free spare. The plasma freguency of the propagation medium is defined as

f 2 2 / 2

20 that iuy/- -

Insert ion of numerical values yields f4 N 9Ie H? where F. is measured in Hz and %, is thenumtr of free electrons per m

3.

Note that w = n when the wave frequency f = fN, and therefore a wave vertically incident upon theirnosphere is reflected at the height where f = 9VN-. The highest freguency which can he reflected cr-tirally from the layer is called the critical freguency

f 5 ,/%e "''

max

where % is the maximum electron density. Freguencies f ) f. will penetrate the laver. A wavemax

incident obliguelv at an ai (le I will he reflected at a helght where

sinlv /1- n =r

aol the highest frequency which can be reflected is f 9,rW cosT = f cosl . This freuency is.may e 0 0 omay

of course, always qreater than the critical freguencv fn.

figure 5 illustrates schematically how the electron density and the refractive index may vary in asimple ionospheric layer, and the ray path throuqh the laver. The wave incident at an angle, I isreflected back to the qround at a distance d. The maximum freguiene which can reach this distance isfmx = f 'coal . If there are no denser ionospheric lavers at qreater heights, this frenuency is themayMaximum seablg Frequency (MUF) for the circuit with pathlenqth d along the earth's surface. Freoun-ries greater than the M1F will penetrate the laver at the angle of incidence I . It is possible to showthat th-, wave will behave as if it had travelled along 'he trianqular path indcated in !he figure andhad bee, -lected at a virtual height h'. - prtnr we understand that the 14F for a particularcir- ue derived from simple considerations, if the critical freouencv of the layer at the reflec-ti, is known.

Figure 6 shows the results of ravtracinq for three frequencies in a model laver with critical fre-ouencv f 4 Wz and Ne at a heiqht of 300 km. The fiqure clearly demonstrates that for a frenuency

maxf > f athe wave cannot he reflected back to the qround at distances shorter than a minimum range,

called the skip distance. Near this distance there is a focusinq effect because waves with differentpenetration depths into the ionouphere converge.

So far we have only discussed wave refraction, but the ionospheric plasma also acts as anabsorbing medium. The electrons oscillatinq in the incident wavefield reradiates the energv transferredto them from the field, unless their oscillatory motion is disturbed by cvllisions with the much heavierneutral molecules and positive ions. Such collisions will convert electromagnetic wave enerqv into

thermal enerqv in the qas, and the wavefield will he attenuated. It is possible to show that the

absorption of a hiih frequency radio wave, measured in desibels, is

A L f I. N vds dbf s

where v is the collision frenuency of an electron, , is the refractive index, and intenrat ion is alono

the ray path. We note that A is inversely proportional to the snuare of the wave frequency. and thatthe contribution of the inteqral to A is laoe where u is small and where N v is laers. LOure 3 showsthat N has a maximum in the D-reoinn where, normally, - 1. this contrigution to the absorption israIled the non-deviative absorption. Absorption occurrinq near the reflection point where L - I Iscalled tte deviative absorption. For obolijue propaoatinn the non-deviative term usually dominates.

The simple model of propa4ation sketched above may he extended to include the effects of theearth's maonetic field, the earth's curvature and the presence nf several reflectino layers. Theearth's maqnetic field makes the ionosphere birefrinoent, that is an incident radio wave spflsup !ntottwo maqneto-ionic components, called the ordinary and extraordinary waves. The ordlnar wavecorresponds most closely to the no-field case, whereas the extraordinarv wa%e has a laroer critica! 're-

luenciv and is reflected at a different level. The absorption for the two components mav estimated h,fquation '7) reolacino the wave frenuency f with an effective freovuencv ftf where + refers to t ,e irhI-nary and - to the extraordinary wave. / f cost where f is the ovro freqLuencv of the ele:t ri."the earth's field and I is the anqle between the direction of propacation andnote from Fouation (7) that the extraordinary wave is more heavily Absnrted an the or,icfar, wawe.

ordinary wave will therefore be the important component as far as Hr-communicat inns are concerned.

The complex structure of the real ionosphere makes many different modes of prroat ilt iuss itSome examples are sketched in fiGure '.

%ote that the total field at the receiver may he a vector sum nf man tlifferert -do-, i,

oround wave which is important at shorter dist ances. The refract ive index of the irojod ma -e '

expressed as

2 180n = r-i -- a

-t

where r is the permitivitv, f is oiven in W*k and c the urvidutiyitv in fiemens m. 1n- , 1'peu',upon the propert ies of the soil, and when n is known the reflect inq and at t enuat ion nroo,,rt , n'surface may be derived.

3. DATA PTAST OF AVAILARLF [PRSERVATTInNS

Since the presence of ionized layers in the upper atmosphere was experment

al Iv est atil Ilhel t,Appleton and Rarnett '1q9di and Preit and tlve '1926', a lare database of ionospheric oseruAt ncy-; hasqraually been compiled to live a olobal picture of the structure of the ionosphere and its vriat inns.The picture is by no means complete; the problem of mappino the behavtour if the ionosphere is ;milarto the problem of mappinQ the weather in the lower atmosphere. More, and mire accurae knowledo]e i,always needed, both from a scientific point of view, and from the communicators point of view as theneed arises for ever more efficient use of the freouencv band ivailable for ionospheric communications.

Under the auspices of the International Council for Scientific Unions "IC}). several World DataCenters for the collection and exchange of oeophvsical data have been estalished. The two most impor-tant are W)DCA in the liSA and '*CR in the ISSR, but in addition a number of specialized renters exist inother countries. These latter centers emphasize special analysis of data relevant to different di-ipli-nes 'Pilqqott A Rawer 1972,.

Two international bodies, ISI and CrIR, are of particular importance in the work n collectionand evaluation of ionospheric data for communication purposes.

tRS| 'International Scientific Radio Union) deals with the scientific aspects of radih wave propa-

qation, mnd is responsible for the lonosonde Network Advisors Group 'INAG: which coordinates ionosondeobservations 'see below) on An international basis. CTIR )Interrational Radio Consltative committee

,

has the International Telecommunecation Union (IT1 as its parent body, and promotes international stan-dardization of models for the propaqation medium and radio noise environment. Much internat lonalcooperation is also beinq stimulated by the Inter-Itnion Commission For Solar-Terrestria: Phyqics(IlIrSTP) which promotes intensive studies of particular phenomena.

3.1 Observationa] techniOues

The lonoest time series of ionospheric data stems from qround based otservat ions. The most

important techniques used are:

a) The ionosonde, which in its common form is a vertically directed pulRe,' radar, measures the delaytime of the reflected siqnals in the frequency ranqe 1-20 MHz. This delay time is converted to avirtual heiqht h' of the ionosphere. Fioure 8 showa an example of an h''f) record, or ionoqram.The heiqhts and critical frequencies of the (- and F-reqions can he read directly from the ionoqram,and by means of fairly comples computations, the h'(f) record may be converted to an electron den-sity profile Ne (h).

54

b) Absorption measurementsThe A! method measures the amplitude of pulsed HF signals reflected verticall, from the layeru. TheA2 method measures the amplitude, at the ground, of VHF radio noise incident upon the earth from the

alaxy. The receiving instrument is railed a riometer (Relative Ionospheric fpaclti meter). 5

ladlnnoise above the critical frequency of the F-laver will penetrate the ionosphere, as the earth ro'a

tes

and the receivinq antenna sweeps across the sky, a "ouiet day" variation of signal intensii will hPrecorded. The noise will stiffer absorption in the lower ionosphere, and a disturbance in theD-reqion will be recorded as a deviation from the oUiet day curve. The riometer is A part irlarlvuseful instrument in the disturbed high latitude ionosphere. The A3 method measures the siginalstrength of a NN F or HF signal reflected from the ionosphere at oblioue Incidence, tnlcallv overpaths of a few hundred kilometers.

r) The incoherent scatter technique involves the use of very powerful, qensitive and sophisticated iH

or UHF-radars which detect weak reflections from plasma irregularit ies. There are ooil a few suchinstallations in operation, but they have provided a wealth of informat inn about innospheri- para-meters.

Figure 9 shows a map of the distribution of ionospheric observatories. As might he expeted, mostof them are located in northern hemisphere, and the large ocea s and polar regions are not well -o rir.

The space age introduced rockets and satellites as platforms for ionospheric ohqerat lors. Inchetflights can yield valuable detailed "snapshots" of ionosoheric conditions, whereas ,atellites have 'esuccessfully used to obtain global coverage of some "top-side" ionospheric parameters. The satIllite-borne "top-side" innosondes have been particularly important in global mapping of F-layer eletr,-' te -sities above the maximum of the layer. Unfortunately the tnp-side ionograms ealv rarely ield ar--rt,values of the F-layer critical frequencies. Their usefulness in filling in naps left mpen in t'-,e .ir,.-based network is therefore limited.

3.2 The ionospheric data

The ionosonde data are conveniently surmarized in daily "f-plots", an example of whir" i pi',, i-figure 10. An example of the lon term variation of critical frenrienries is shown in figuro 11, wJe-clearly demonstrates the 11 year cycle present in the ionospheric parameters. As will he diuosetlater, this solar cycle dependence is important for prediction purposes. The lta hase mra he set t,construct contour maps of ionospheric parameters. An example figure 12 shows a map of fo12 the r f it-cal frequency of the F-layer) compiled for the east zone from datA for 4n stations -or two solar o sl(Reddy et al 1979).

After mere than SO years of ionospheric observat ions it is fair to state that the hehavir r" te

undisturbed mid-latitude and low-latitude F- and F-reqions is adeoluatelv mapped for mar rommunirat iOpurposes. Then are, however, important gaps in our knowledge of ionospheric hehaviour durino distirharl-ces, and in general the high latitude ionospheres are not well understond. 'here is also a larL nfdata, on a global scale, on the structure and behaviour of the lowest part of the ionosphere, the D-reqion.

3.3 The conducting propertips of the earth's surface

The conductivity of the earth's surface is of importance for the antenna gain at the transmitterand receiver sites, and for ground reflections in mutltihop propagation. There is therefore a need forglobal conductivity maps, and for some applications there is also a need for terrain modelling. Presentmodels distinguish between land and sea conduct ivities, using average values of the reflect ion coef-ficients, but the inclusion of more detailed maps of ground conductivity would improve propagation pro-dirt ions. 'See section 9)

3.4 The radio noise environment

An HF-signal must he detected against a hackground of radio noise from natural and man-made sour-Pes. The first compilation of radio noise data was carried out by Railev X Kojan '1Q43). riIR 'Report322 1963) has prepared an atlas of radio noise intensities based uipon measurements obtained mainly from16 stations throughout the world during an international cooperative programme. flats were collectedFrom these stations from 1957 to 1961 and the noise power versus freqiuenry are presented in diagramssuch as figure 13.

The natural radio noise has two important sources, atmospheric lightning discharges, and oalqrtircosmic noise. A stroke of lightning produces noise over a wide frequency band, with maximum intensitynear 10 kHz. The noise from the thunderstorm activity throughout the world, in part icular from thethunder-storm centers in fquatorial Africa, Central America and the Fast Indies, will propagate to greatdistances through multiple reflections between the earth and the ionosphere. The galactic noisepenetrates the ionosphere from above at frequencies above the critical Freguency of the F-layer, an

t is

in general the dominating noise above about 2f W7?. The man-made HF-noise may be important inindustrial or densily populated areas, and may have large local variations.

Contour maps of radio noise intensity, such as figure 14 are available for different times of daysnd season.

4. InNOSPHERI MIDELS

Ionospheric modelling for HF-communication purposes aims at a description of the ionosphere Andits variations in time and space, which allows prediction of propagation parameters. The model must

therefore be simple enough to be practical, and sufficiently complete and accurate to he useful. The

degree of complexity and sophistication in a model depends upon the requirements and resources of theuser, and the practical solution is always a compromise between the needs for simplicity and for

accuracy. There are two different approaches to the modelling of ionospheric circuits. The first is to

fit empirical equations to measurements of signal characteristics for different times and paths, the

other is to estimate these characteristics in terms of a number of separate factors known to influence

the signal (Bradley 1979), such as critical frequencies, laver heights, absorption etc. When a large

data base exist for a particular circuit, the former may he useful, but it lacks generalitv. The second

approach has the advantage that a limited data hase can be combined with knowledge of ph,sical prin-

ciples to ouide a description of the behaviour of the ionnspheric layers.

The first approach has been successfully applied to medium freuency 'F' propagation, whereas itis generally agreed that the second method is the most effiLcient one for HF propagation.

4.1 Modelling of the ionospheric layers

If the ionospheric electron density height profile is known at every point along a propsoa ion

path, the signal characteristics at the receiver may be calculated using some form of ravtracing proce-

dure. A useful approximation is to neglect variations alono the path and assume that the profile at the

reflection point (or points if there are more than one hop) may he timed in the rastracinl. The prohlem

is then to describe this profile in terms of a few measurable parameeprs, so that the raytracing

through the simplified model ionosphere yields realistic signal characteristics, for vertical incidence

ravtracinq should reproduce an ionoqram typical for the time and location nf the reflect ion point.

Figure 1" shows four electron density models in order of increasing rnmplexity. The model in

Figure Pta includes the F and F-laser only, as simple paraholic lavers with specified critical freotien-

cies, heights and thicknesses. This model is used in the first PIR predict inn orocdure 'FCI 'TP'

and is at present still recommended by (CIR. A second CFIR procedure is in preparat inn rf[P 1018 and

the electron density model is shown in Figure T h. As will he seen, the gap between the F- and F-lxAvr

has been filled in, so that the electron densitv in,-reases linearly with helht in this lnterredlatp

region. The two CFIR models have been discussed in some detail hy Rradle% '1'9 .

Figure 15c shows a model used in a recent method "Ionospheric Analyiis and Prediction" 'Ip fAp

developed at the Institute for Telecnmmunicat inn Sriencies 1) loyd et al 1qR2. The region between the

F- and f-layer maxima is now even more complex, including a "valley" and two linear seoments. This

figure also shows a virtual height profile, and demonstrates that the model can reproduce the mostimportant features of an innoqram, including an Fl-laver. Note that the inPCAP includes a simple model

of the D-reqion. All three models make some provision for the presence of sporadic F-layers.

Finally F igure 1id shows the electron density profile adopted in the International Reference

Inosphere (II, Rawer 191R).

The IR has been developed by a task group chaired by K Rawer, under the auspices of 1195T and

rnSPAR foemittee for Space Research). The International Reference Ionosphere is described hi Rawer'1991). It represents a compendium of height profiles through the ionosphere of the four main plasma

parameters: plasma density, plasma temperature of elec'rons and ions, and ion composition. These

parameters are geterated from reliable data including hoth around based, rocket and satellite data, xnd

the IRI is thus primarily an experimental, not a theoretical model. A computer code generates height

profiles for any time of day, position and sunspot number.

The 1I electron density profile models all ionojspheric layers and is nite complex. It has

therefore not vet been adopted or recommended by CIR for HF-communication predictinns. Raytracinq

through such a sophisticated profile would require complex computer codes, and it remains to be tested

whether the Added complexity yields real improvements of predicition accuracy.

a. 2 flobal modelling of key factors

gnce a model of the ionospheric layers, sich as those described in the preceding section, has beenchosen, a model of the temporal and spatial variations of the key factors describing the vonospheric

structure mist be decided upon. The diurnal, seasonal and sunspot cycle variations of peak plasma den-

sities and heiqhts have been modelled by ('IR 419671, hased upon original publications by Jones and

Gallet (1960, 1962. The model or atlas is based upon grotnd based measurements exclusively, and is

available as a computer tape. As an example of such modelling, Figure 16 shows measured values of nooncritical frequencies versus sunspot number. The sunspot cycle dependence is modelled by linear inter-

polation between values of critical frequencies at smoothed sunspot numbers R12 n T and 912 z Inn. The

diurnal and seasonal variations are modelled in terms of the solar zenith Annle X, which, of course, is

readily calculated.

The original Jones and Gallet model gave a description in terms nf geographic coordinates, but it

was found that inclusion of the earth's magnetic field in terms Of a "modified dip coordinate" (Rawer1963) improved the consistency of the charts. A model of the earth's magnetic field is therefore also

essential in a description of the ionospheric layers. The rrIR model is also used as a hasis for the

International Reference Ionosphere in its global mapping of peak plasma densities and heights. As men-

tioned above, satellite data have not yet been included for these parameters, although the IR ime sucrh

data to model the shpEe of the electron density profile above the f-laver peak. A spesific effort by

CCIR to include satellite data is in progress.

4.3 Modellinq of ionospheric absorption

We have shown that most of the ionospheric absorption of HF-waves occurs in the P-reqion. 0-reqion electron densities are, however, small and difficult to measure, and the ionospheric loss is

therefore normally modelled by moans of empirical equations based upon absorption measurempnts. The

ahsorption of the ordinary wave may be written (Rudden 1966)

1 N vds

L = const - , e (91

ff2) ,v1)IL '2s

(see ,ention 2.3) where inteoration is along the ray path. For vertical incidence we may write

1(f) v A(f) )dR} in(f 2 )2+v 2

where A(f) is a constant when 1 1 1 (non-deviative absorption but has a frequency dependence near thereflection point where ui << 1. The models are based upon estimates of A'f') from measurements of absorp-

tion. The ('1IR ab'- ption equation is based upon studies by Lait inen and Haudon '1950) and Iucas and

Haydnn )1966), ano the empirical equation for obligue incidence is

L(f) =677.2 1 se 11'

(f+fI )1.9810o2

where f0 is the anqle of incidence at 100 kin, and the frequencies are qiven in M-z

-2.937(f.844S fof

The factor I thus contains the solar zenith anqle and sunspot cycle dependence throuqh the F-laver

critical frequency foF. The term A(f) is represented by an average value A = 677.2 1. An important

effort to improve the absorption model has been made by Georqe f1971) who includes a frequency depen-

dence of A~f). this method has heen extended and used for absorption modellinq in the iONIAP predictionmethod (Lioyd et al 1981). Models of ionospheric absorption such as those mentioned above have proveduseful in low and middle latitudes, hut becomes inadequate in latitudes beyond about 600, where theabsorption is larqe and varies rapidly. An "excess system loss" factor has been included in the models

to account for the lat itudital vaziation in hiqh latitudes.

4.4 Statistical description of the ionosphere

The ionosphere has siqnificant day-to-day variations, The data base provides input to the modelsin terms of monthly median values of the ionospheric parameters and a statistical distrihution aroundthe medians, for esample as quartile and decile values. These statistical parameters have been includedin the prediction models to provide estimates of the probability distribution of siqnal characteristics.

S, THf PRIN'IPLF nfl HF-PRFDIrTIONS

The principle of all physical predictions is, of course, extrapolation of past experience into thefuture. In the precedinq section we have described models nf the propaqation medium which allows esti-

mates to he made of the state of the medium at a certain location, solar activity as indicated by the

stunspot number and solar elevation. Py predictinq the sunspot number at a future time, we may thereforepredict the state of the ionosphere. The state of the sun is heinq monitored continuously from solarobservations throuqhout the world, and reasonably reliable data are available for a period of more than

200 years. Modern observatories issue reqular lnnq-term 'months, years) predictions of solar activityas measured by the sunspot number. These predictions of monthly values are based upon eatrapolat ion ofpast "smoothed" sunspot numbers, allowinq for the well established 11 year cycle in solar activity.Short term predictions of the development of Solar disturbances are also issued for periods of hours anddays. These allow predictions of "effective" sunspot numbers which ran he used in HF-predictionmodellinq. (See comparinion lecture).

In this section we shall not discuss solar physics and prediction of solar conditions, but ratherreview the procedures used to estimate the reliability of a communication circuit once the probablestate of the ionosphere has been established by predictions. We shall nly deal with lonq term predic-

tions here.

A frequency prediction service aims at providing the user with estimates of the circuit reliabi-lity as a 'unction of frequency and time. The useful ranqe of frequencies is limited at the hiqh fre-nuency end by the path ilF, that is the hiqhest maximum useable frequency of any possible propaqationmode, and at the low frequency end (lowest useable frequency ltIF) by the presence of noise and possihlescreenino by the F-laver. The siqnal to noise ratio mist he evaltated at each frequency within this

ranqe. The procedure may he summarized as follows:

a) Determination of the path MUFFirst the points alonq the circuit must be found for which ionospheric information is needed. Forpath lenqths less than 4000 km the path midpoint is used. For longer paths two "control points",2000 Lo from either end of the circuit are found, and ionospheric conditions determined at thesepoints. The "control point method" has no rigorously proved basis, but seems to work well for manyapplications. Given the ionospheric model, the 14JF may be determined by raytracinq, or by using ML4Ffactors (M(D)). These factors are defined as:

MUF (sinqle hop, distance D) = fo.M(D) (12)

Such factors may be derived from ionograms and are tabulated for the different layers by CI.R(196?). Fioure 17 shows an example of 14F factors.

The path PIJF is the highest of the MJF's derived for the separate layers, and the lowest of the PtlFsfor the two control points.

The more sophisticated rastracing procedures such as that used in InNCAP allows determination of anarea coveraqe, that is the area of the earth's surface illuminated via the ionosphere at each fre-Quency. (See Fiqure 4).

h) "etermination of siqnal strenqthWhen the -odes that can exist are determined, the power received at the receiver location for eachmode is

Pr = Pt+GR-Lh r

where Pt is the transmitted power, ft and Flp are the Gains of the transmitting and recei inq anten-nas respectively at the elevation anqle corresponding to the mode in question, and th is thetransmission loss. Ih may include many terms, such as free space loss, focusing effects,ionospheric absorption (see section 4.3 and ground reflection loss. The ground reflection loss Ismodelled by CrIR by the conductivity of the surface at the ground reflection point. The conduc-tivity depend; upon frequency, and five reference values for fresh water, sea water, wet ground,medium dry qround and dry qround or ice have been chosen. loss due to polarization fadLng, sporadicF and over-the-MUF reflections may also he added. The rms skywave field strength F dA above1 uV m

-lt is given in terms of Pr by

F = Pr 2n loqf+l7.2 (Ti'

when f in the wave frequency in MHz.

c' Determination of signal to noise ratinThe noise charts and a knowledge of manmade noise conditions at the receiver site yield noise poweras a function of frequencv. For a given band width h of the receiver, the noise field strength Tnmay he determined

( Fn = f,-6

%.+20 loqf.1t logh 15'h

where Fa is the noise fiqure given in CU[R report 322.

The siqnal to noise ratio in desihels is then 5NR = F-Fn.

d) When a required signal-to-noise ratio is specified, the statistical propert v if the ionosphericmodel and the noise model may be used to determine the mean reliahility of the ,su sit for a givenmonth.

5.1 Some available prediction methods

We have discussed methods for lonq term 'months, Years) predictions of HF propaqatinn conditions,and several such methods, implemented on digital computers, have received recent international atten-tion. It may be useful to mention some of the most important here. These are 252-2, SUJP 252, I[NrAP,MtIFlttF, FT/, TWM, YlF and IIt 252.

The rCIR recognized method is contained in rrlR Report 252-2 and is recommended by the rrl foruse until SUIP 252, supplement to report 252-2, is completed in computerized form and tested. Roth uti-lize a tao-parabola ionospheric model and an ionospheric loss equation derived from the world datacenter data base.

The IONCAP proqram forecasts for the distribution of the siqnal-to-noise ratio at freguencies from2 to 5S MHz. The model considers the F, Sporadic F, FT and F2 layers, usinq an explicit electron den-sity profile. The basic ionospheric loss equation is the rrIR 252-2 supplemented by the F laver, Fslayer and over-the-MUF considerations. A separate method is included for very long distances.

The P4FLUF, FT/ (Damboldt 197S) and ItL 252 programs were submitted to the IWP (Interim WorkinqParty) 6/12 of the CCIR for consideration of use by international HF broadcasters (CCIR, ITti, Geneva).They are considerably smaller programs than 252-2, SUP 252 and IONCAP, hence are specialized in applica-tion.

The FM YLF is base I on CCIR 252-2 with simplifications made in the field strength probabilitycalculations.

U_

4comjari son of cmpter "-re vi/e cciirw mei and 'omittational time 'or a sample rtn of 1 mont',

12 hours, i rciiits mitt a t frerienc ps has been male tin 1 m)r a't H-Pi computer.

111/f I I t , Y EONlS

252-2 27.4

ttIP2 2 0rS K 1" .4llt AP ih K 27.4

MIIF LIF 24 K .5

F/ O K I.I ii 2'7 T K 1.4

NOTf: No direct comparison of HFM lI was availhlp at this writ inn: however comparison made bfly YlIesradio Ah, Helsinki on a Cvper 175' Computer showed HEM Yt required 24.

q seconds of rin

t imp compared to "n.i seconds for IIP 2,Z, method t.

table 1 i'omparison of qome available prediction prorIrams

The Applab Ill program Rradlev 19751 has heen produced b the Appleton lahoratory in the IJk. It

is similar in size and performance to the SlIP 252, but is not ident ira] to this procedure.

The above table illustrates the differene in complexity of the differeot aailahle mode!s. Their si/euant runnioq times; are determined, essentially, by the quest ions thp are developed to ans wer, arid the

sophistiratinn of the methods usPd. thp choice of method will depend upon the reoriirements arid r-sir-ces of the user.

,. I IMITAIION (IF THE PRDtt'TIIN METHODS

The arcracv of the predictions is limited for several reasons. firstly the database qives iiiat-

qorte coveraqe of marry parts of the qlobe. fyamples are the polar reoinns and the larie oceans. Thismay have the consequence that important spatial structures are neglected. Spcondly the ionn sthere is

hiqhly variable in time, and munthly medians of propaqat ion parameters may not always be useful to thecommunicator. Again this problem is particularly difficult in high latitudes. Thirily nur knowledue ii'

the physical processes that govern ionospheric oehavioiir are oot aleOtiate for urutinu the viudellint; if

propaqat ion throiTh the medium. %evertheless, tests show that durin undisturbed ciniOt ions schemes

qivp reasorably arsrate results. The perhnrmanrp deeriorates markedly at lat ittides ah~ie 60o.

We have shown that the state of the ionosphere rteiirids upofn solar act i ltV, y rd that ssrst predic-

tion mettitns Isp mrouthed %s.espot nJmber as a driving ftunction to determine the paramaters nf the

ionospheric lavers. The sunspot ntumber is an empirical indes of solar activity, aid it is not always a1

qood measure of the effects of the sun and tune interplanetary medium rin the ionosphere. Our

undecstandunq of the physical processes that determine this rompler interact ion is not suifficiprt; Iv

advanced to make reliable predictions for longer periods ywars'.

7. THE tIS (IF PRFIII'TtNS IN 1% T'fM INIATIIN AN) SySTIM PAN %f,

In this section we shall Lse the TONCI' predict ion method to illustrate its ariplicat ion for -nm-

munication and system planning purposes.

Let us first consider the problems of a user of an established circuit who needs to chonse the

optimum frequency from hour to hour and day to day. HP iir she knows the basic performance parameter of

the system, such as transmitter power, antenna gains, rpotuirPd siqnal to noise ratio etc. A mnthlvprediction may then be issued in the simple form of a table of reluat:littys as a function of frequency

and time of day. table 2 shows an eample of such predictions. The path IIFs are ilver separately,with their corresponding reliahilities. The predictions may also he given in the form rf a iraph, such

as in Figure 18, where lIlF, li and fVO are plotted versus time of day. IiF and FDT freuence Optimum

de Travail) are the lowest and highest frequencies respectively with an availability of 0.9. From such

qraphs the available frequency range is readily found for any time of day.

The system planner will need more information than is readily available from the simple outputs

.jut described. He will need to know which modes are dominant at different times for different freine-cies and the corresponding elevatinn angles of the rays, so that efficient antennas may be chosen. Prn-

pagation delay times and the relative signal strengths of different modes are also useful parameters

allowing estimates of multipath interference to h made. The planner will also need to know the rangeof losses to be expected so that the minimum transmitter power needed to obtain a certain required

reliability can be estimated. Propagation estimates mist therefore be made for a range of conditionscovering diurnal, seasonal and solar cycle changes.

The IONCAP will provide such users with computer outputs of the form shown in Table 3.

I. THE 11S Of THE HF SPEtrRUM

The Hf-spectrum is a valuable natural resource Which must he shared monqst many users with very

different needs and technical capabilities. Interference from other users of the H-band is one of themajor problems in HF comamunicat ions. Modern technology offers many Tssihilities of improving the effi-

ciency of HiF-communication systems. Some of these will he discussed in other lectures in this series.

The basic principles must he to radiate the energy in the optimum direction, to radiate as little energy

as possible, and to choose an efficient modulation technique in order to minimize the hand widt or thetransmission duration. Automatic transmitter power control, antenna steerino in azilmuth and el[Pat tan,frequency sharing in time multiplex amonqst several users, are all possihle wavs to on in future lese-

lopments of HF-techniques. It seems obvious that improved prediction technioues will he ,aluahlp tools

in improving the overall efficiency of IF-communications.

9. HF-COMINICATIONS VIA GROtIND WAVF

HF-communication via ground wave is important in many areas, particularly over sea and flat landwith high conductivities, where reliable circuits may be established up to distances at several huindredkilometers. The conductivity of the surface is stronqlv frequency dependent with rapid attenuation atthe higher frequencies. In the past CCIR has published a set of curves of arnund wave field strenothversus distance. An example is shown in Figure lq. rFIR (1978' is in the coirse of implementinn a an-

puter program to estimate ground wave field strengths. Ground wave propagation may he aute camplev,particularly over rouoh terruin and over mixed land-sea paths. There is a need for better charts ofground conductivity, and in some cases terrain modelling may he useful and important. large topooraphi-cal features such as mountain ranges and glaciers may cause reflections and strona attenuation, andvegetation, soil humidity and snow cover also influence the propagation characteristic s.

10. rtNClt lSItNS

A review has been made of the state of the Art

of h oropanat ion model1inq and predict inn.Although present day models have reached a high degree of sophist icat ion and complexity there is roomfor major improvements in many areas. The development of the data base nf ionospheric parameters hasbeen slow, in particular in the inclusion of satellite data in the models. As a consequence there are

large "white" areas in the world map of the ionosphere, I e the large oceans and the polar relioas. Thedetailed modelling of an important parameter stich as the availahle bandwidth of an ionospheric propaja-tion channel has not been given much attention. This parameter is certainly of interest for the "ge s fmodern modulation techniques, such as spread spiectrum modulat ion.

REFERFNCFS

Appleton, f.V., Barnett, M.A.F. (1926). "OCn Wircless Interference Phenomenon between rround Waves andWaves deviated by the tpper Atmosphere". Proc Ro Soc A 113, 4flO.

Bradley, P.A. (1975). Lonq term -- propaqation prpdict inns for radio circuit planning. Radio and

flectronic Engineer 45, 31.

Rradley, P.A. (1979). Propagation at medium and high frenuencies, 1: Practical radio systems andmodelling needs. AGARD lecture Series %o 99, 1-1.

Bradley, P.A. (197"). Propagation at medium And high frenuenries; lno and short trm models. AGAR

Lecture Series No 99, 9-1.

reit, G., Tuve, M.A. (1926). A test of the existence of the conductino laver. Phys Rev ZR, 554.

Rudden, K.G. (1962). Radio waves in the ionosphere. rambridqe tiniversitv Press.

CCIR (1963). World distribution and characteristics of atmospheric radio noise. Report 322 Doc of Xth

Plenary Ass, ITI reneva.

CCIR (1966). CCIR Atlas of ionospheric characteristics. Report 340, [oe" of XTth Plenary Ass, ITit Deneva

CCIR (197g). Interim method for estimating sky-wave field strenoths and transmission loss at freonQen-pies between the approximate limits of 2 and 3l MHz. Report 2,2-2, Doc of X11th Plenary Ass, IlT

Geneva.

rCIR (1978). Second (fIR computer-based interim method for estimating sky-wave field strength andtransmission loss at frequencies between 2 and 30 M4,. Sunl to Report 2'2-2. Doc of XIVth Plenary

Ass, ITtJ Geneva.

Croft, T.A. (1969). A review of oblique ray tracing and its application to the calculations of signalstrength. Fd I B Jones, AGARD Conf Proc 13, 137.

Damholdt, 1. (1980). Propagation Prediction of the HF-ranqe by the Research Institute of the DeutscheRundespost, in Solar Terr Predict. Proc, Fd R F Donnelly. ItS Dept of Commerce 1, 25.

Davies, K. (1965). Ionospheric Radio Propagation, NBS Monograph 80. US Gvt Printinq office.

Davies, K. (1969). lonoapheric radio waves, Blaidell Publ Co, Waltham, Mass.

George, P.L. (1971). the global morphology of the quantity JNvdh in the D- and f-regions of the

ionosphere. J Atmos Terr Phys 33, 1893.

FRI-79 (7981). International Reference Ionosphere World Date Center A, Report IAG-82, Fd K Rawer,

Boulder USA.

Jonea, W.H., Gallet, R.M. (1960). Ionospheric mapping by numerical methods. ITO Telecommunication

Journal 27, 260.

Jons, .P. tallt, A.M 1962. Th ersentation of diurnal and gteographical ionospheric data bynumerical methods. ITO Telecom JOUrn 29, 129.

laitinen, P.fl., Haydon, 17.W. (1950). Analysis and prediction of sky-a~e field intensities in the highfreguency band. 11r Army Signal Radio Propagat ion Agency Tech Rep No 'Q, Rev 'RPN201'.

I ied, F., Friksen, K.W., (andmark, P., mehlum, R.N., Thrane, F.V. 1967 : High freotiencv radio com-munications withi emphasis oni polar problems, AG7ARDonraph 104, lechnivision. Maintenhead. fooland.

Illoyd, 1.1.-, 4aydon, r.W., Lucas, D.1 ., Teters, L.R. (1981). Estimating the performance of telecom-municat ion svstems using the ionospheric transmission channel. Institute for rele--ommeuiratir,Sciences Report, Roulder, Colo RF330 USA.

Lucas, D.L., Haydon, tl.W. Predicting the statistical Performance indlexes for high freqtiencv telecom-municat ion systems. FSSA Tech Report IfRi-IfSAI, 09 tvt Printino Office, Washington DC1.

Piggot , W.R., Rawer, X. (1972). IIRSI Handbook for lonoqlram Interpretation and Reduction. World Datarenter A, Report LAt-23.

Rawer, K. '?9A3). Propaqation of teoameter waves !Ilf-ban&, pp 221-251), no Meterolooi-al and 4stron--mica) influence oo Radio Wa~e Propacat ion, Pergamon Press, Oxford.

Reddy, P.M., Aggarwal, %., Iakshmi, O.R., Shastri, S., Mitca, A.P. 'tR199. longi term solar activity andionospheric prediction services rendered by the National Physical Laboratory. %ew Dehli. Solar-Terrestrial Predictions, Proceedings 1, 118, 119 Dept of C'ommerce, NOAA Pouilder.

11E II In 24 I0QICAP 19.qi

MAR 199.5SS 1/.

OSLO TO LO'AO')l A 'TMI)TH q1 KM1

54.9Z V ?115 Ei - 57.51) N .-11 6 2.? tl9 ?.4 19.1 I114UM ANGLF S.101 r r, fF S

ITS- 1 ANi I KA PACKAi.X TRt 1.') TI i1., IPORI. ilelLE 14 -. ;'j L -. ) A 010 n OFF A5 1.0'tlmIA I. T7 11. H.)ay. )IPOtf 1 -. ?5 L -. S51 A fl.1 OFF A7 1. 1POWER 1 1.00q .1 S 1147 Nut F -14R.0 rtOW "El. wFL = q0i DEQ. 9148 16. 1

F9R(1 ItA t / RE) IA4ILITY

CITt LMT i~h ? . . 3 .1 9j5.(j1. 5 11.)q 17. 1s.1(I1 17.9S ?(i. 1 ?5.n0 11.0 UF

1) 7.;1 (.2 Qq0 :') .96 . 5? .0 ,1 .- *11 :nn1 .nn .7

'.. 4. 5 : . -5 : Q4 .5; I ) 1 '1 111 "11 .10 fl .11 W n n D'tn

t. I. 11.1 Oi'l .1)1 .9 * .5 .1.?S 1' IT n00 -in .0n it1

10 . 1 10.1 1'.)4 . 1 .. 1' . IJ .1 1S A9 .60 44e 140 "1 .11 *?4

l.l 14./1 14. . 1 &1 I : I1 71) .? 1 ? .70 .45 11 .1 .00 . s116 1 14. 1I 5 / 1 1 1? .ii. 1 f,/ I6 .98 '-I !'I .0 R91

18.1 le. ?1 . 4 I11 .45 .,i1 .7% Iti .j? .1/ 1 .1o ioon . ?1i I. 1 2l.( t .' Q1 j1 )9 I4 ./ 7.9 .16 A .11 t 1 .1, .c RJR22.01 2,7 7 ?/ t., t 4 t5 .5 1 ) .12 q 0 j0 .10 nof in on K9

table 2 Reliability verxuxs frenuencyr and time of dlay For March 1981 for the criit Oslo-fooonr.The reliability is defined ax the Probability that the signal-tc-noifse ratio SNP exceedsthe reguired ';NR for the service. The xuinspnt nuimber is 555% = 77. the minimusm angle ofelevation for the antenna is specified ax 30.* Horizontal half wave dipaoe are specifiedFor both transinitter andi receiver with heights above orouindl 114 wavelenoth. (H =0.25 A,I z O.S A). Transmitter powepr ix 1 kW, and the man-made noise level at the receiver siteix takepn As -148R dRW, correspnding to "rural" environment. The renuired signial-to-noiseratio, Pen SNR, is the ratio in decibels of the houirly median x;ional Power in the occulpiedbandwidth to the hourly median noise in a 1 H, bandwidith. It is9 here specified ax SNPR99 dl), correspondlin to A signal-toi-noise ratio of 25) rIl for a channel with 1 k"? band-width. The term Reg Rel is used for l(OF calciat inns.

-4 gTJkIn 235 T IN rtA 7X n 54A W 94 -

",AH 1903 451.' = //.

() TOOT I )1 A 7 T'IJT 14 N.M ~T K

TS- 1 O TrF A ,'4EA,,5

('TN 3. Tf ,5I . 'I ot. 7 1'LI- ? - 5 1 - .' A 0. n ,TFF A7 1.RlC ?.,I TO >') 0?. H IPAL , -. 25 I -.53 A 0.0 0r A7 1.1

) 1.'' . i -H? Nif -14.1' 1 ' '). 3F1 * Io Q. 4.4 = V4.1

-f 1 4 if

12l. 1 14.4 .' 1s . r. 11 2 1. 5 15. 1 1 1.5 tiP 24. 3. FQ EIF? I ' IF' IF? IF? IF? IF? IF' it? IF? MI E20. 6( . 4, 1. . .L ,1 . i 1 ) . 1 '0.7 ?0.7 20 ') . 0 ? 20./ 1 A -LE

3/s. PA. ?t . 4 I I ' 5. ' J?. !2P;. 1 5. S 715. 54S. V -4!T T6 . -3". -21. 41. 5. '44 4

o . 4. '). 44. S. -15. 4'5

1).~~~~ 11 f 'iM R. .. 4. i. 'P1 t 3 044S./, *'tl ." .14 *2) .'4 .014 .?3 "$ ff1 . 11 01g QF

L

'. , . % . S.', t'; .w 11.1 12.5 l .1 it S 21.2 24.' Ff.' F 1P)1f? f I i? It? 1F 1' 1F? F I iF'I F? iF? I F" '9P E4,.. 4'..' 25t,. 1 2.1 3A4 5f..4 3 4 .1 14. 1 4..4 4 /.1. 4.134.4 A IiGtI

4''. 11 ii 4 . 41 .'0. 15'. 4 n 1 . 5rlt. 4o1. 441". V MIrE. L I4. /. tA. 35. A2 2* -1. -1. -" . I1. NP

Tahlp 3 Out put option useful for svst em planitr, -howinrl po-nile ion-phcerir mode, withcorrispon dino elevation anoles. The ;irtaL'Rj PIoht cf the reflPtlrnq laer and the

siqnal-to-noiP ratio for each mode are liven. The term PPWPC I, tle requredil nombiati n

of transmitter power and antenna lain, in rtf, needed to achieP the ranuiired reliahililt.For explanatinn of other terms. lee Table 2.

hlkm)

300- F2- lae

200.20C Fl-layer

E-layer .- :z= Sporadic

100 D-region E-layer

D- reg Ion

105 toS Ne cm "3

Fluire 1 A typical undisturbed davtime electron densitv distrihution. To the riloht the fiqure

indicates which wRvelenoth hands are absorbed at different heinhts. The F- and F-reoions

normallv show clear masxima, bereas the F1 renion IsR A ledOP in the profile.

c 5 D2

F ER

1

/A2

.8 "(411 1 2 N ~

IN 1 1 . '01 Oa 1 06 ' N

iore Tvpr njec heit fnionrhO ins r \,,t evc ron r Os' 'sc F4Ir.,

nr a lied hen r da t im aonl soanq. i rele , ar-rK w to n',- 1c 1e

p T

orr

Rd arspho I, W- ii 45 l r,rl '4.,l 1I,'n1 . " ' ''r 'r

rofrat IVO, p, I'll

F 2 -F2

E -- - -E

2) F2 mode b, M -mode

C 1 E + 1 F2 mode d) Mode in an ionosPhere with tilts

' A,

4vl -T- ,

-a-r f - a S *n

l~r'H t,pjr I i nn sn,,I rPr iinn W1 t tc nrr'snn-,ll I n P I Pr'trT(IF rIrns, It 1

Ic I ' I i ,

IONOSPHERIC VERTICAL SOUNDING STATIONST- 0 - 959 DATA IN WDC- a'

I : 196! DATA IN WDC-AL

. ... W , .. . . ... ... .,,. . .

C J . . . .. . .- i.q-i - **+

• 4', ........ ....-, " . . . • 0. . .. ..*. . . . . . . . . . . , , -, . .t . . . . .

: ii'. ,. I A I; ' * ,

"t .. .' :4._; " ... . . . it;". . . .W . .

.. . .. . : r . ... g . .... ... .. . ... .

. --...............-.. .. . . . . . C.,C C .r~ 7 C C C "C ) .. ..~

.1 w P [ e~r- o 1 t 1

A~ lilU :A ........

:N NI At MR....

I E

'Ill ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ A " N ' c'I rf i;! ~ ;p n; ,c -- , ~ p i ~ ~ ,39'

J 931'3233 '34 '35 '36 '37 '38 '39 '40 '41 42 '43 '44 '45'46 '4

1949 '50 '5! 52 '53 '54 '55 '56 '57 '51 '59 '60 '61 '62 '61

F r winpr t e rn vatr iat rnrrr; of r iticalI frerrjr,r 1n at flinirh ib Pl-,n OPSi 1 19,

Finrt 12 A rrOntour map of foF2 in W47 fnr the east zrine ',OOFl~ 17OF4 for SePopmber 1977 Rredlr PtaI 1179).

I.IN

14 ..-

-:: :A.

25- ., .. .

211

2'2r,

F iore 14 Pontour map of Fa at I Wti for Winter flttlfl-2flf tne-A time.

I~mF2 -

III

I-I

i

y-y - -

EI mE,

0 foE foF2 foE f J7

Ca) PItsmo freqenCy 1b1

F iq,,r V '' \,h' model fnr ripR fir0t prn-duire rlr 7,h' %,'h h",rdnl f-r rr p. .... . r.,,tri .

HEiOT, ktIVIRTUAL

T dTopsrde rI }

TRU

h) EVST Inteyed 1I

m , ' LINEAR (wr PARABOLICI LEDGE

-- HEF

LINEAR VALLEY HME - HABR

EPARABOLIC NOSE IHDX E/L6

y _ I Hd)

EXPONENTIAL TAIL {

IfE fo, 'oFa NME NMlF2

FREQUENCYlog N

Fioure 11c) Ne(h) model Lsed in the IoNr'AP Finure 15d) N,(hl model uSPd in the Inter-procedure natinonl Reference Ionoqphpre.

1 o:SS '"WSW' C= 4LY 44 - 4L $41SS DE3RAS*GM-

--..

9 *""' **.t (q s

6 -

4 . .......

2T

0 26 40 60 0'0 00o 120 140 iO6-0 j 200

SUNSPOT NO-

Fiur 16 CritI~I freowI,,,i,' of ioo~ph'T1

aIs ~rq rs O'oothpd St~nspotntmher fnaloI' Q6s.

E

4 F

23F

0 1000 2000 3000 401X)0

Ground1 rangqeKm

Finijre 17 RIsF Factrs For .qinoJe hop F, F1 andu

F2 rofleptinns JRradley 1979).

'iFTi1D 2$4 SONCAP 7R.Is

4A8 103 -;-I = 7/. K

aSLO To O 1J4 87 Al'4'THS Pd. mi. (S9.Q? Nj 19.15c 51 .51 '4 .04 w 2 fI.52 51 .34 6??.6 1153.0

*l-tMUl ALE 5. n O1E4'RTE5I rS- 1 8 1144118 PACKAGEXm1Il 2.,4 T) 3r. n 0HZ. IIPOLE H -. 15 c -. 51 A n.1 OF F A47 1PCVR 2.1 TO 31) n i'3)R ?. )T Po 0 p -. ?S L -. 5 an A rh OFF 4T 00n

S I. 1.) K. PillH %ojv f = -144.kJ fleiw 44U1. QAL or, RtO. cqs9 55,

*11 n2 14 to -1 1 1 12 14 16 18 2'7 22 "

16- -16

14- -- 1'

12- -12 rNT MU F FOT LUF

? A .1 6. ? 4.6 .1 _.4 f 5 . 5 4 : 7 2 0

6 / 0 11.1 Ro -1

D3 Q 1. 13. 4 10.2 0.6- ') 1. 14.4 11I.8

016- 9 -6 14.0 14. 3 1 1.1 -

16IS.0 14.1 11.0 /.0'14: Ft * n :. ~ 25 ?.n 4.8

+ ? 00 7 6,. 2.?712. +/ * + -12 2?.0 * 5.1 2.1

- ?4.0 6. 5 4.6 2..j

nol '2 04 n6 .14 1 1 1 Z 14' 16 13 1f ?2 ?00U NI V E RSAL T I r

Fiqture 18 RAIF, [LW and rnT from IC1NCAP predictions for the circuit Thin-london.

120-

100 -

E60-

A40- 500kEz

V

2- 0 MHz3 NMi

0 - IMMz

-20-

1 10 10 10000, km

FzInure 19 Ground wave field strengthi versus distance for c 4, mid a =lfl3 8 m-1

(Aradlpv 1979).

REAL-TIME CHANNEL EVALUATION

byM.Darnell

Senior LecturerDepartment of Electronics

University of YorkHeslington

York YOI 5DDUK

SUMMARY

The requirement for real-time channel evaluation (RTCE) in HF systems isidentified and discussed in detail. Various scenarios in which RTCE is applicable areexamined and classified.

Specific RTCE techniques and systems are then described including:

- Pulse/modulated pulse sounding- Chirp sounding- Limited channel monitoring- Interference characterisation- In-band RTCE

The application of RTCE to practical HF systems isdiscussed and the benefitsaccruing from its use quantified.

INTRODUCTION

As has been pointed out in a previous lecture (Darnell, 1983), real-timechannel evaluation (RTCE), in the context of HF communications, corresponds to th,-process of system identification, or propagation path modelling, which mjst becarried out prior to the application of optimal control strategies. The classicalmethod of controlling HF circuits involves the use of off-line propagation analysiscoupled with operator experience; to this end, sophisticated propagation analysisprograms have been developed to provide the basic data required for HF system control(Haydon et al, 1976). Although such progra'n can predict long-term path parameters,say on a monthly median basis, with reasonable accuracy, their short-term precisionis limited. Thus, they are better suited to providing data for system planning -ndfrequency assignment where analyses over complete seasonal and sunspot cycles ar-required.

The aim of off-line propagation analysis procedures is to provide frequencyselection data which will give the communicator a 90% probability of satisfactorycommunication at any time, assuming that the basic characteristics of thecommunications system, eg transmitter power, antenna types, etc, have been correctlyspecified in the system design. Typically, the frequency selection data would beprovided in the form of an optimum working frequency (OWF) on an hour-by-hour basis.Although propagation analysis programs are being continuously refined, they havecertain fundamental limitations which lead to off-line OWF predictions beingadequate, rather than optimum, for many purposes; the most important of theseshortcomings are:

(a) The effects of interference from other spectrum users arenot included in the analysis and prediction model)

(b) The propagation data base used for computation of predictedcircuit performance is limited;

(c) The significant effects of perturbations such as suddenionospheric disturbances (SID's), ionospheric storms andpolar cap events (PCE's) cannot, by their very nature, betaken into account in the analysis;

(d) The effects of relatively transient propagation phenomenasuch as sporadic E-layer refraction, can only be describedapproximately;

(e) The "confidence level" for the OWF predictions is normallyonly 90%.

To overcome some of the above limitations in long-termionospheric forecasting techniques, short-term forecasting techniques have also beendeveloped. These involve real-time observations of solar and ionospheric parameters,together with feedback concerning which frequencies are propagating at a given timeon selected circuits. Clearly, these procedures will tend to overcome some of thedata base restrictions of the long-term forecasts; however, the following pointsshould be noted:

(a) Correction data can only be provided on the basis of sampledreal-time conditions and therefore will not be uniformlyaccurate for all links;

(b) There are logistic and economic problems associated with thetimely dissemination of the correction data;

(c) In general, the corrections do not indicate which of a set

of assigned channels is likely to provide the bestgrade of s,-rvice;

(d) As with long-term forecasting techniques, the effects ofmanmad- interferinq signals are not indicated.

For the reasons listed above, off-line propagation analysis cannot normallyprovide circuit parameter forecasts with a degree of confidence required for HFcommunication where high reliability and availability is essential. Accordingly,increasinoi kmphasis is beini given to methods 'or charact-rising HF channelsaccurately in real-time, le RTCE.

2. THE NATURE' OF HTCE

There are two basic sources of signal distortion associated with HF paths, i-time and frequency dispersion. The combined effects of these two distortionmechanisms can be represented by the "channel scattering function", a typical exampleof which is shown in Fig. 1. In essence, this function shows the dispersive effectsof the channel on an ideal impulse in the time domain and on a single frequency CWtone in the frequency domain. In the example illustrated, three discrete propagationmodes are shown: these might arise from refraction by different ionospheric layersand/or multiple refractions from individual layers. A given scattering function willonly be a valid description of the channel for a specific transmission frequency andover an interval during which the "dispersion surfaces" remain sensibly constant.However, it is not necessary for a communicator or HF system controller to know whatdetailed, fundamental, physical principles give rise to the propagation phenomenawhich affect the performance of the communication system - that is the task of theionospheric physicist: rather, that person should have access to the parameters of anappropriate real-time model which describes the path behaviour adequately. This modeldata can then be used to control the operation of the system and to adapt optimallythe signal generation and processing algorithms.

A definition of RTCE (Darnell, 1978), now adopted by CCIR (CCIR, 1981), is:

"Real-time channel evaluation is the term used to describe the processes of measuringappropriate parameters of a set of communication channels in real-time and ofemploying the data thus obtained to describe quantitatively the states of thosechannels and hence their relative capabilities for passing a given class, or classes,of communication traffic".

As a result of the above definition, the following points should be noted:

(a) The RTCE process is essentially one of deriving a numericalmodel for each individual channel in a form which canreadily be employed for p-formance prediction and systemcontrol purposes.

(b) A particular RTCE algorithm must generate a channel model ina form appropriate to the class, or classes, of trafficwhich it is required to transmit over the channel. Forexample, a channel model required for 75 bits/s telegraphywould normally be expected to be considerably less complexthan that for a 2.4 kbits/s digitised speech link.

(c) The term "real-time" implies that the measured channelparameter values are updated at intervals which are lessthan the overall response time of the communication systemto control inputs. If measurements are made t ore frequently,the information cannot be employed effectively by thecommunication system and is thus redundant.

(d) The output of the RTCE process, in the form of an estimateof the relative capabilities of a set of channels to passvarious forms of traffic, must be expressed in terms whichare meaningful to the communicator and system controller, ega predicted error rate for digital data or a level ofintelligibility for analogue speech. In an earlier lecture(Darnell, 1983), it was shown that RTCE is an essentialprerequisite for the application of automatic system controlprocedures.

(e) RTCE is not simply concerned with more accurate and timelymonitoring of HF propagation conditions, but also withcharacterising the effects of interference from otherspectrum users. This is particularly important because,inmany instances, it is interference which is the factorlimiting communication system performance, rather thanpropagation.

(f) Also, as was shown previously (Darnell, 1983), in additionto providing information on the optimum frequency fortransmission, RTCE should ideally give an indication of theoptimum start times and durations of transmissions.

(g) In the form defined above, RTCE will not simply selectchannels propagating via "conventional" ionospheric modesbut will also make use of more transient modes, eg sporadicE-layer refraction and meteor burst, if appropriate.

Most channel models generated by practical RTCE systems are related to thechannel scattering function and tend to fall into either the time Iomain or frequencydomain category, depending upon the nature of the signals to be passed over theassociated communication link.

3. A GENERALISED RTCE ALGORITHM

It is assumed that the state of any HF communications channel can becharacterised by a set of n distinct measurable parameters which are functi-ns ofboth frequency f and time t, ie

pl(f, t" I p2(f, t" , ....... I Pn(f, t) (i)

This set of parameters can be expressed as a column vector(P(f, t), where(/pl f, t(P f, to (p2)f, tI•~' ) (2)

pn(f0, t)

The definition of RTCE implies that the channel parameters will be sampled i, aconstant rate consistent with the minimum response time of the communication system;let this sampling interval be T and the number of alternative channels in theavailable set be m. Hence, at the k th sampling instant when

t = kT (3)

and for the i th frequency channel of the set for which

f = fi (i integer 1 < i 4 m) (4)

expression (2) becomes: ( l (kT)(P~kT) 2 kT)P (5))

f Pn(kT) I fi 5

Now, defining an "RTCE weighting" matrix as the row matrix(A)where:

(A) = (a1 a2 ...... an) (6)

Iand an RTCE "figure of merit", Qa' for the i th channel as:

Qa (kT) J (A)(E(kT() (

Therefore

Qa(kT n = [alpl(kT) + .... + anPn(kT)l if

As will be discussed later in this lecture, in practical RTCE schemes only oneof the parameters pl, P2, ... Pn is normally employed as the basis of measurement;thus the RTCE weighting matrix reduces to:

(A)=(0 0 0 .... 0 aj 0 .... 0 0 0) (9)

(j integer I < j < n)

and the figure of merit is given by:

Qa(kT)1

La Pj(kT10)fi fi

In addition to the use of the sampled values of the set of measurable param ,rsfor RTCE purposes, the various time derivatives of those parameters may also besampled and used to characterise the behaviour of the channels with time. Forexample, a column vector of first time derivatives of the n parameters and acorresponding row vector of RTCE weighting coefficients can be defined in a similarmanner, ie

f ii

andniT)

fi

"-I

(b) h2 ...... b ) (12)

Th- corresponding TCE. igure of merit for the i th channel is ths:

Qb (kT) (kr)) (13)

Again, in practical RTCE systems, the weighting mat'Iix will take tle form:

= ( 0 0 .... bj .... ooo) (14)

Other figures of merit employing higher order time deivatives can be intrrslucedif appropriate. The overall channel selection decision will in general d-pend upon aw,-ighted combination of the various figures of merit which will be termed the

"channel pref-rence factor" (CPF), where

CPF(kF) i F( Qa(kT), Qb(kT)..........I (15)

= FI(Ak (kr),(sj (kT) . ..... (161

The nature of the partinilar RTCF algorithm used in any given situation willdetermine the form of combining function F{ } and of the weighting matricos (A),(B),etc. However, in general, their form will be influenced primarily by:

(a) the com,nuniations objectives of the syst-'- which the RTCealgorithm is intended to support, eg whether sinle mod,propagation is necessary, whether the maximum possiblesignal-to-noise ratio (SNP) is required, what'loctromagnetic compatibilityconstraints ha;

- to be

satisfied, etc;(b) The capabilities and limitations of the available RF and

procossing equipment.

Ph-' ovr.rall function of the RCE system, therefore, is to comrut the CPF foreach member of the set of m available channels, ic

CPF(kr) I for I .< i < m (17)

andi then to sol.ct the value, or val eq, of i for which the" CPF is a masimim. Afurther important function )F the RTCF process may be to rank the rmaining channelsof the set in order of preforence in order to id-nt iFy. possible stand-by ,hannel .

Therefore, in its simplest form, a g,neraIisd STcE algorithm may be reprse teddiagramatical y as shown in Fig. 2 with the" , ur basic, inputs of

- propagation lata- interference/nois data- communication systm oljectiven- ,quipmemt ,har-cr ristics.

In a more d-tai led form, the general ised STCF algorithm discussed above can berepresented by the schematic arrangom,rnit illustratod it. Fig. 3, for parlmeters andtheir first derivatives.

4. SCFNARPOS FOR THE APPLICATlON OF RTCF

Three practical HF communication scenarios in which RPT(' tecoiques at'-applicable will now be discussed ()arnel1, 1975):

4.1 Class I RTCF: kemote transmi ttod Signa I Pr -processing

Fig. 4 shows a block diagram of what will be termed a Class I RTCE system. It isapplicable to the situation in which a r *,nPot or robile t-.rminal wishes to passtraffic to a base station on a random or scheduled basis. An RCE probing signa l,s(t), is transmitted at appropriate intervals over the HF channel from the basestation. Apart from spectral occupancy and EMC constraints, there is no limitationipon the form of x(t). Sperialised processing eguinment at the rmote terminal!)erforms an analysis of the received version of the RTCE signal, yft), and hen,".fomulatps an appropriate path Iclel. In the moelling process, RTC information fromother sources can be incc-poratt'd if available, eg via the analysis of other RTCprobing signals from sepa-ate sources, data transmitted to the remot- t,rminal viaother propagation media such as satellites or VLF, etc. The model is then sejd toderive control data for pra-processing the rmote transmitted signal, r~ti, to yilda signal, r'(tI, which is subsequently transmitted over tho channel and receivd itthe base as r")t). Ideally

r"(t) = r(t - d) (18)

--e . _ _ - . - _ i . i n n mm l m n mln f l

where d is the effective prcpagation delay. It is clear that his type of RTCE ar.iprocessing necessitates in assumption of propagation reciprc ity, :? the profaqaonmodel for the base-to-remote path is an adequate descriptin of the remote-ro-basepath also. Normally, this premise is reasonably accurate, provided that allowanc. ismade for any differences in chara eristics between baseand r.mote ransn-itter,receiver and antenna configurations.

4.2 Class Ii RTCE: Base Transmitted Signal Pre-processing

The basic block diagram of a Class II RTCE system is given as Fig. 5. Inessence, the technique employs base station single-site RTCE in order to d-termine anappropriate pre-processing algorithm for communications transmissions from that basestation to remote stations in defined locations. The RTCE probina signal, x(t), isradiated by the base transmitter; energy returned from the channel to the base in theform of a signal y(t) is then employed to formulate an appropriate channel model. Themodel is then used to derive the pre-processing algorithm which is applied to th,base transmission, r(t), to give a signal rl(t). Note that r'(t) and x(t) may bemultiplexed if operationally convenient. At the remote terminal, the siqnal r'ti isreeeived as r"(t) and again ideally

r"(t) r (t - d) (lq

where d is the propagation delay. It is also possible for the RTCF modell nq rcessto make ise of data from other sources, eg by monitoring transmissions from otherstations in the vicinity of the remote terminal(s). In practice, Class II RTCE isapplicable to broadcast type systems.

4.3 Class III RTCE: Remote Received Signal Processing

Fig. 6 shows the general format of a Class III R]CF system. As in the case ofClass 1 RBTCE, the RTCE probing signal, x(t), and the bas- station traffic signal,r(t), are multiplexed prior to transmission over the HF channel. At the remoteterminal, the received RTCE signal, y(t), is demultiplexed, processed and thenemployed to form a model of the channel which is subsequently used to control thesignal processing strategy to be applied to the distorted version of the trafficsignal, r'(t), to produce the corrected traffic estimate, r"(t). Again, the objectiveis to make this estimate identical with the original traffic signal. Once more, RTCEdata from other sources can be incorporated into the model formulation process.

The scenarios outlined above describe open loop situations in which traffic flowis basically unidirectional. In many practical cases, bidirectional traffic flow willbe required and thus equipment of say the Class I or Class Ill types might have to beprovided at hoth terminals. Alternatively, the availability of feedback between theterminals in the form of a low-rate engineering order wire (EOW) would enhance theflexibility of the procedures and allow RTCE data to be transferred between receiverand transmitter. However, for reliability, the EOW itself would also require someform of RTCE. Auxiliary inputs to the RTCE process in the form of data passed viaseparate communications media, relay from other remote terminals, interpolation orextrapolation using other RTCF probing transmissions, etc, should always be soughtto increase reliability.

5. PRACTICAL RTCE SYSTEMS

To date, many different F(erms of RTCE systems have be-n developed, making use ofa variety of measurable parameters. Examples of specific parameters on which RTCEalgorithms have been, or could be, based are:

(a) Signal amplitude;(b) Signal frequency7;(c) Signal phase (absolute or differential);(d) Propagation time (absolute or relative);(e) Noise or interference level;(f) Channel impulse response function;(g) Signal-to-noise or signal-to-interference ratio;(h) Energy distribution within the channel bandwidth;(i) Received digital data error rate;(j) Received speech intelligibility level;(k) Telegraph distortion factor;(I) Rate of repeat requests in an ARQ system.

Examples of RTCE systems which have been developed to at least a workingprototype stage will now be described in the following sections. In general,practical RTCE systems fall into three basic categories:

Those which operate on any frequency in the HF band, onthe assumption that they cause negligible interferenceto other spectrum users;

Those which operate only in the frequency channelsassigned to the communication systems which they aredesigned to support;

Those which operate within a single assigned channelwhich may, or may not, be passing nommunicationtraffic.

Systems falling in the first of these categories will now be discussed.

6. RTCE SYSTEMS NOT CONSTRAINED TO OPERATE IN ASSIGNED CHANNELS

6.1 Pulse Sounding

The pulse sounding technique was originally developed as an aid to fundamentalionospheric research, with its value as an RTCE tool only being appreciated at Ilater stage. Pulse sounders require dedicated transmitters and receivers operatina onthe basis of time and frequency synchronism. A high power sounding transmitterradiates short pulses in a pre-determined time sequence on a large tjmber ofspecified frequencies covering part, or the whole, of the HF band. Thq-time'frequencyschedule is under the control of the system program, which must be identical for bothtransmitter and receiver. The program timing is controlled by mast-r clocks attransmitter and receiver; these independent clocks can themselves be synchroisgd bymeans of an external standard time transmission such as MSF or WWV, with appropriat

.,

allowance being made for differences in propagation tin- to the two sit's.Alternatively, the requirement for alignment using an ext,rnal standard can beeliminated if atomic clocks are available at the both transmitter and receiver.

If the transmitted pulse, x(t), is of short duration, the response of thesounding receiver corresponds to an approximate channel inulse r sr-nsq- fnr .ac' ofthe m channels on which a transmission is made. The received signal is giv.n by th-convolution integral

y(t) = h(u) x(t - u) du (20)-~ I f 11' i'

where h(u) is the unit impulse response function of the channel and u is i tLx.

variable. If x(t) is an approximate impulse, then y(t) is evidently proportional tothe impulse response function h(t). One way of overcoming very rapid variations inthe response is to transmit several pulses on each channel and compute an averageresponse.

The output intormation from an ionospheric sounder is normally presented in theform of a visual display termed an "ionogram", which is essentially a two-dimonsionalprojection of a raster of impulse responses for the m channels, as illustrated inFig. 7. Fig. 7(a) shows typical impulse responses, indicating the pr 31senc odifferent degrees of multipath propagation, taken from the complete m-channel irray;Fig. 7(b) is a projection of this raster, in the sense indicated, which forms th-ionogram display of ionospheric mode structure in the propagation d. lay (d) -frequency plane. In the RTCE context, the ionogram can then b uied to select say aregion of single-mode propagation having minimum time dispersion - as shown in Fig.7(b). Alternatively, if no region of single mode propagation can be identified, a CPFfor each channel could take the form:

CPF = Ene r in stronqest mod e (21)L Tota energy in al -dsJ if

The more nearly the CPF approaches unity, the closer propagation would be to singlemode. Allowance would also have to be made for the relative total energies in thepropagating channels to ensure that an adequate SNR was maintained.

6.2 Modulated Pulse Sounding

An important practical modification to the basic pulse sounding techniquedescribed above is to apply digital modulation to each of the transmitted pulses inorder to increase the signal processing efficiency of the system. This processprovides two important performance enhancements:

(a) It enables pulse compression coding to be applied (in thesame way as in some types of radar) in order to improve thetime resolution of the system without having to resort toshorter pulses, and hence increased peak transmitter powers.For a given time resolution and quality of impulse response,it is necessary to use a certain amount of transmittedenergy to prob, the channel;for unmodulated pulses, thisenergy must be applied in the form of short-duration, highamplitude pulses whilst, with pulse compression modulation,the energy can be applied at lower amplitude over a muchlonger interval, but still achieving the required timeresolution.

(b) The RTCE transmission can be encoded with small amounts ofdata via manipulation of the pulse modulation, eg todescribe noise/interference levels in assigned channels atthe transmitter site.

Several forms of pulse compression codinq have been developed; these :nclueBarker codes (Barker, 1953), Huffman sequences (Coil & Storey, 1964), binary"sequences of length > 13 bits with autocorrelation functions (acf's) approximatinq toan impulse (Mann, 1968) and complementary sequences (Darnell, 1975). With all theseforms of modulating signal, the impulse response of a given channel is obtained bycomputing the input-output crosscorrelation function (ccf). For a linear system withinput x(t), output V(t) and unit impulse response function h(t), the input-outputcc f, dxy(t), is given by (Lee, 1960,:

+TI/2

= I/T' fx(t) y(t + Z ) dt (22)

-T1/2

h(u) d xx - u( du (23)

where 'rand u are time variables, T' is the correlation interval and txx(l

) is the

input icf. Using expression (23), it can be seen that if the input acf is anapproximate impulse, then the ccf xy() will be approximately proportional to thesystem impulse response function.

Ionospheric pulse sounding is a widely-used method of RTCF; man,. individualsounders exist for specific communication paths, but relatively few networks have yetbeen implemented. Possibly the most ambitious pulse sounding scheme designed to datewas the Common Iser Radio Transmission System (CURTS) (Probst, 1968), in which anetwork of pulse sounding transmitters was set up giving complete area coverage forall user- with compatible sounding receivers. CURTS is an example of a Class I RTCEsystem.

6.3 Chirp Sounding

It is also possible to employ a fundamentally different technique known as"chirp" sounding to obtain an ionogram display: as its name implies, chirp soundingmakes use of a swept-frequency transmission as a channel probing signal (Barry &Fenwick, 1965). The sweep is typically linear with tim-, but may take other forms.Again, synchronisation between transmitter and receiver is necessary. Fig. 8illustrates the principle of the technique: in a multipath propagation situation,several weighted versions of the transmitted sweep will be received as shown. If acorrectly timed local oscillator sweep is available at the receiving site, this can.e mixed with the incoming sweep components to y,2d the difference frequencycomponents which are then subjected to spectral analysis.

At time tk, the frequency of the synchronised local oscillator sweep is

fmin + d-f t k (24)dt

whilst the corresponding frequencies of the received component sweeps are

fmin + df (tk - A't1 ) (25)dt

fmin + df (tk - At 2 ) (26)dt

fmin + df (tk - At 3 ) (27)dt

After mixing with the local oscillator signal, the frequency components of thedifference signal are:

At 1 df At 2 dS At 3 df (28)dt dt dt

Hence, propagation delays are translated directly into frequency offsets. Assumingthat the mixing process is linear, the relative amplitudes of the individual receivedsweep comp- Rnts will he preserved. Time dispersion due to the distributed nature ofthe ionospi tic refraction process will cause the received sweep components to bebroadened aday from ideal spectral lines. Therefore, if the mixer output is displayedon a spectrum analyser, a propagation mode profile equivalent to the channel impulseresponse will result; taking a projection of the spectrum analyser output as afunction of local oscillator frequency will again yield an ionogram.

6.4 Modes of Operation for Ionospheric Sounders

The ionospheric sounding systems described in the previous three sections can beoperated in oblique incidence, vertical incidence or backscatter modes.

Oblique incidence Implies that the sounding transmitter and receiver aregeographically separated so that the transmitted energy impingts upon the ionosphericlayers obliquely. This form of sounding can thus be used as the basis of a Class I or

Class Ill RTCE system.

Vertical incidence sounding employs a transmitter and r.,cer whi'n ar.- 0-sited. The sounding transmissions are directed vertically ipwards at the ioos her,in order to determine its structure just above the sounding site. Oblique d.-,characteristics may be inferred from vertical incidence measurements. This tv. )fsingle-site RTCE is therefore well suited to Cl1 ; I1 scenarios.

Backscatter s9unding is similar in character to vertical incidence sounding 1-that it can be cirried out from a single site, or closely spaced transmti1"r inireceiver sites. However, th- transmitted energy is now radiated obliquely rath:r thinvertically to enable the ionospheric structure in a desired direction of provagationto be evaluated. The received signal arises from energy which has been rofra-m 7d bythe ionosphere over a path away from th, transmitter, reflected from the. ... h'ssurface, and then propagates back to the receiver via a similar ionosph-rie-refraction in the reverse sense. The technique is normally only applicable to singl.hop paths since multiple hops give rise to e..ssiv

- received signal attenuation.

Also, the received scattered energy is at a much lower level than with vertical oroblique incidence propagation, thus necessitating much higher radiated powers andgiving poorer definition. Backscatter sounding is clearly applicable to Class II RTCEscenarios.

7. RTCE SYSTEMS CONSTRAINED TO OPERATE IN ASSIGNED CHANNELS

Whereas the RTCE systems described in the previous sections are designed to

operate anywhere in the HF band on the assumption that the interference they cause toother users of the spectrum will be negligible, there are other forms of RTCFspecifically intended to function only in the channels assigned for use by thecommunication systems which they are reqiird to support. Since the assumption ofnegligible interference by ionospheric sounders is questionable, often beingcritically dependent upon the nature of the transmission being interfered with, thelatter class of RTCE systems would appear to have more potential for widespreadapplication in future by virtue of its more efficient spectrum utilisation; also, asdiscussed in an earlier lecture (Darnell, 1983), such systems would tend to employthe same RF and processing units as used by the communication syu-,r, thus resultingin economy of implementation.

7.1 Channel Evaluation and Calling (CHEC) System

The CHEC system was developed in Canada to improve the reliability ofcommunication between long-range maritime patrol aircraft and ground stations, withthe emphasis being placed upon the air-to-ground link (Stevens, 1968). CHEC wasdesigned for a situation where one or more mobiles are required to pass traffic to abase station. On each of the m ,ssigned channels, where m would normally be < 20, theCHEC base transmitter radiates in sequence a probing signal of several seconds'duration comprising a selective calling code, data on the average noise level at thebase station in that channel, together with a CW section. At the remote receiveralerted by the selective calling code, the base station average noise levels

nt) 1 (29)i l i (m

for the subset of k channels actually propagating to the mobile are decoded to give

nt) I (30Ifj where j can take any k distinct values

in the range 1 to m and k < m

The subset of corresponding average received signal levels at the mobile

A7t) ( 31 )

are evaluated using the CW sections of the base transmissions. Thus, by assumingpropagation reciprocity and also making allowanct: for differences in antenna gainsand transmitter powers between base and minbil, a processor at the mobile computs, Apredicted average signal-to-noise ratio for its own transmissions propaqatin q to th'base in each of the k channels. Therefore

SNR(t)bas. It (32)

where G is a channo dependent factor to compensate for the diff-rences in antnnaand transmitter characteristics between base and mobile. The optimum chann-l formobile-to-bas, communication is then given by the value of j for which the SNR is amaximum. In experimental form, CHEC was shown to give significant improvements inchannel availability and reliability.

Other systems, similar in concept to CHFC but applicable to differ.,ntoperational requirements, have been devised, eg a ship-shore system employed by ASWin the UK (Wynne, 19791 and the Canadian radio telephone with automatic 'hannelevaluation (RACE) system (Chow et al, 1981). The practical situations in which CHEC-

d'

t y, - h av been eroli jd correspond o the Clss I -scenario defined in Se,-t ion4.

7.2 RTC5

by Pi I-t Ton, Phase Measurements

ITn this m-triod, the RTCE probing signal is a simple CW pilot tone ins-rted at asitable position in the transmission channol bandwid1th (Betts & Darns1l, 19751. TheIa ;is of the ea l uat inn procedure is that, after detection of the pilot ,on, in anirrow bandi issf ilt.,r at the rec.iver, its phase variations are analysed and useod toin ,.r the siitahi lity of the channel for the transmission of various types of trafficby making use of analytical relationships between phase instability and data -rrorra

t..

In th .. xperimentaI system, the phas2 of the raceived pilot tone is comparedwith that if a locally-genrated refcrence phase iource . This phase diff,rence is-tttpiei, at r-qular intervals, typically 10 ms, and the phase oifference at the'irr-nt sittling instant, an, compared with the phase diff-rence measured and stored

N' th., inr.(l,.9 ig instant,'n- 1 Ideally, this phase differen-,' should h.' t,robit for practical channels will normally be non-zero; if the difference in phas,herwen the two sami,11s e.xceds a certain pr.st threshold val ue, At, a "phase -rror"is c-,n t od, ic

An - n-) t 133)

r a phase error.

Clarly, if is necessary that the impl ing interval should be In integralnl t i ple of the pilot tone p-triod in order that sampling takes place a- the same

tain- in the pi lot tone -ycle uinder ideal condi t. ions.

Th parameter slectoed to indicat- the st.ate of the channel is the number o-ph tue 'rror occurring in a prdetermined measurem,nt interval, typically 100 to 200seconds. For practical tests of the system, a low-level pilot tone was frequency1l t iplexrd with a 2-ton-,, frequency-exchan (e k ye, (FEt 3)7 ti t/s bi nary lataignaIl, as illustrated in Fig. 9. By appropriate calibration, the number of pilot

t one- phas, err ors ''an be related to the number of lata bit errors over the samenaslrment interval. The theoretical rlationships for steady signal, flat fadingind frequency-selective fading ar shown as silid line in Fig. 10. The pointssujp.,ri 1,5)so0 upon those theoretical plots r-,pr.-sent masured valtes and indicate th"tyi'-al scatter obtained during an experimental run.

The main conclusion which could be drawn from a comprehensive series of testswan hat, for the great majority of channel conditions oncountered, the data orrorrai. which would be experienced using a given transmission sch.-me over a particularpath could be predicted with reasonable aeciracy via simpl, phase masurements onlow-level CW pilot tones. Thus, this lat'-r parimer'r coild be used directly toestablish a C1F.

Pilot tone RTCP could he ised in a Clas I scenario where a mobi le requi res tocommunicate with a base station; pilot t,nes could be radiated by a single widebandbase station transmitter at low level (typically a few watts) simultaneously on allchannels assigned for mobilo-to-baseo transmission which were clear of interf'rnce atthe base. Hence, as shown in Fig. 11, the mobile would he able to mak' phase errorrate m'asarements on all channels propagating to it from the base: in the same way asfor CHF', propagation reciproci ty would he assumed and allowance made for thedifferent transmitter and antenna charatristics it the two sites in order topredict the channel likely to yield the maximum SNR at the base. The disadvantage ofthe long evaluation time for the pilot tone method could be offset in some situationsby its extreme simplicity of implementation.

7.3 RTCE by Error Counting

A simple form of RTCE is to probe the m channels to be evaluated by means of atest signal having essentially th, same format as the 'raffic signal to be passedover the path. It is convenient practi,ally if the RTCE signal is digital so thaterrors can be counted, rather than having to make more subjective ass-essments orquantities such as speech intelligibility. The essential r-quirement is again one ofproviding transmission and reception systems synchronised in both time and frequency,although the accuracy of synchronisation necessary is somewhat less than that for anionospheric sounding system.

For digital traffic, the assigned channels can be evaluated in sequence usingexactly the same modulation format as employed by the traffic transmission and thecorresponding error rate measured at the receiv-r; the CPF is ther, related directlyto the measured error rates. This procedar

. is equally valid for data or digitised

speech traffic since the error rate for the latter can also bo interpreted in termsof speech intellibility - as shown by the empirical model for 1.2 kbits/s digitisedspeech given in Fig. 12.

A similar, but less precise, relationship exists between analogue speechintelligibility and data error rate. Fig. 13 shows a baseband spectrum in whichtINCOMPEX-processd spech (Awcock, T9681 is freque-cy multiplexed with low-rate

binary FEK to,,r phy. Fig. 14 i s an e-ni r i al model showing the relat ionship betweeL[NCnMPEX sn ,h intel igibility and I EK i ti .rror rate for repr, Sentative HF ptths;iaqa i ri, the sneech quja i ty cooIld ~er~i93wit h r-asonahl e ace in acy f rom error t Atem.easur.tments a n a simPle digital RTCF signal.

Ther.efore, for all common forms of HF traffic, it appears; feasible o carry oitRTCE via a simpl, error counting proce,lare.rh- main disadvantage of Ihe method is the time taken to accumulate the necessaryerror count in the case of low-rat, data. A technique termed *pseudo-error" countlnghas been proposed to overcome this problem (Leon, 19731; here the error rat,, isartificially amplified by the use of an otvr-sensitive detection method so that therate measured by the RTCE syst-m is substantially greater than that which would noexperienced by the traffic transmission, thus allowing the r-qird error count to beaccumulated more rapidly. Because of the inherently high error rates associated withHF links, and also the rapidly time-varying nature of the received signal, it maywel be difficult to apply pseudo-error counting to HF links 3u- to inaccuracy of

alibration.

Practical trials have been carried out using a basic error counting RTCF systemM-arnell, 1978). Two types nf traffic signal were used:

(a) 75 bits/s FEK telegraphy;(b) 1.2 kbits/s digital data.

Path lengths of 700 km and 1100 km were used in the tests, with 24-hour operation.

The classical method of controlling an HF circuit using off-line propagationanalysis data is to select one daytime operatingfrequency and one night-time frequency, ie 2-frequency working as illustrated inFig.15. The RTCE error counting trials compared the -ircuit availability using thisform of 2-frequency working with that obtained by employing the RTCE data forfrequency selection. on avcrage, it was found that the use of RTCE increased thecircuit availability by approximately 45%. It was evident from the results that thefactor limiting circuit performanco was, in most cases, manmade interference. Thevalue of the RTCE process lay chiefly in its ability to enable the communicator toavoid interfering signals, rather than to track propagation changes.

The RTCE by error counting method is chiefly applicable to Class I scenarios.

8. RTCF SYSTFMS OPFRATING WITHIN A SINGLE ASSIGNED CHANNEL

All the PTCE techniques described in the previous sections have been applicableto situations in which the communicator has available for his use a number ofassigned channels. In many cases, however, a communicator may wish to examine thestate of a particular channel in more detail, eg:

'a) To assess the state of the channel currently carryingtraffic relative to the states of alternative channels;obviously, for a number of reasons, it may not be possibleto employ the sam- RTCE algorithm for evaluating thetraffic-carrying channel as for evaluating stand-bychannels.

(b) To examine the baseband spectrum of a channel to determinewhere within that baseband a narrowband traffic signalshould be placed for minimum error rate.

(c) To determine the optimum signal processing procedures to beapplied to a traffic transmission within the channel bymaking use of an appropriate RTCE model (Class IIIoperation).

Various RTCE techniques applicable to this single assigned channel situation

will now be described.

8.1 In-Band RTCE

The term "in-band RTCE" refers to a technique designed specifically for theevaluation of sub-channels within a nominal 3 kHz assigned channel bandwidth. At thereceiving site, a real-time spectrum analyser monitors the distribution ofnoise/interference energy for all sub-channels within the bandwidth using a set ofhandpass filters. Low-energy regions are identified and indicated to the transmittersite by means of a low-rate FOW; this allows a narrowband traffic spectrum (< 3 kHz)to be adjusted so that the majority of its energy falls in the low noise sub-channels(Darnell, 1979). Studies of narrowband H? interference have indicated that itscharacteristics can only be expected to be relatively static for periods of a fewminutes (Gott & Hillam, 19791; thus it may be necessary to make frequency changesrelatively often. If in-band RTCE can be used to select different parts of anassigned channel as the narrowband interference patterns change, the need to changethe frequency of the transmitter and receiver is avoided, thus improving theefficiency of spectrum utilisation.

8.2 RTCE Using Soft-Decision Information

The term "soft-decision" relates to the confidence level associated with a"hard" digital decision. For example, soft decision information could be obtainedfrom:

(a) Amplitude values of a received signal;(b) Phase margin between a phase reference and phase detected by

a receiver.

Any information which can be extracted from a received signal and subsequently usedto quantify a detection decision confidence level car, in principle, be used for RTCEpurposes.

In a DePSK modem such as KINEPLEX (Mosier & Clabaugh, 1958), the phase marginbetween the received signal phase,

8r(t) , and the locally generated reference phase,

80 (t), could be used as the basis of the CPF, ie

=C = F Jr(t) - eo(t)fAlternatively, the CPF could be a function of both the amplitude of the receivedsignal and its phase margin. Soft-decision data of this type has been incorporatedinto an HF modem known as COOFM (Chase, 1973) to enhance transmission reliability andto enable the modem to reject data blocks not meeting the required confidencecriteria.

8.3 RTCE in ARQ Systems

An ARQ communication system typically formats the data to be transmitted intofixed-length blocks which are then individually labelled. These blocks aretransmitted sequentially until control data derived from soft-decision processing orerror protection decoding indicates that a given block has been decoded erroneouslyat the receiver. "i ARQ signal is then passed to the transmitter site via a f=edbacklink, or EOW, r 4uesting a repeat transmission of the corrupted block. Evidently, thenumber of block repeats requested in a given time interval will be a m-asure ofchannel quality and can be used for RTCE purposes.

8.4 RTCE by Traffic Signal Modification

In some situations, it may be impossible to obtain the required RTCF datadirectl), from the traffic signal, possibly because the soft-decision parameters ar.not accessible or as a result of the traffic being encrypted. In th- latter case, itis possible to modify the format of the traffic by the introduction of additionalsignal generation and processing functions which will facilitate the extraction ofRTCF data.

Possibly the simplest method of accomplishing the necessary modification of the

traffic signal would be to insert an auxiliary, low-level pilot tone at a suitablenull in the baseband spectrum of the traffic signal. Analysis of the pilot tone phase,error rate, as described in Section 7.2, would then allow the data error rate for the

traffic channel to be estimated with reasonable precision.

In certain forms of encrypted data transmission systems, a special errordetection and correction (EDC) process can be introduced in order to yield RTCFinformation to assist in overall system control; Fig. 16 shows such an arrangemen'.It is assumed that security considerations limit access to the element, of thecommunication system except for the region shown. If an auxiliary EDC system, shownhatched, is introduced into this region, it can be used to format the encryptedtraffic into arbitrary codewords prior to transmission. At the receiver, the receivedcodewords will be decoded to yield the original encrypted traffic stream; however,the EDC algorithm can be implemented in such a way that the number of errors beingdetected and corrected can be continuously monitored, thus indicating the state ofthe channel for RTCE purposes.

9. NOISE AND INTERFERENCE CHARACTERIPATION

In previous sections of this lecture, the importance of noise and manmadeinterference in determining HF communication system performance has been stressed. I"areas of high spectral congestion, eg the central region of Europe, it is normallymanmade interference which limits system performance, rather than propagation, whichis relatively predictable. Similarly, with the off-line propagation analysis programsdiscussed in Section 1, one of their major limitations stems from the lack of anadequate model for interference.

It is clear, therefore, that considerable effort must be put into themeasurement and characterisation of interference, both from the point of view of RTCFan, of off-line analysis. In-band RTCE systems of the type discussed in Section 8.1could form the basis of interference assessment systems for incorporation into RTCEprocedures. Other systems can also be used (Cottrell, 1979) (Barry & Fenwick, 1975).

In some cases, the interference assessment will be explicit; in others, such asthe error counting technique described in Section 7.3, the RTCE process evaluates thecombined effects of both propagation and interference in a single measurementprocess.

10. CONCLUSIONS

10.I General

As was pointed out in a previous lecture (Darnell, 1983), the rationil' f-rdevelopment of RTCF techniques is that significant improvements in the use of - iFpropagation medium can only be achi.ved if a communicator, or HF system o -ntrn ,using a specific path at a given time has access to real-time data on th- rel-.vctpath parameters, rather than having to rely on off-line propagation an-ll7gis whichcan be subject to appreciable inaccuracy. In particular, off-line technilit cannever provide accurate information on noise and interference leovl in a qi-,n1channel at a given time - although, with further refinement, they ran well cr-owIde

r-asonable sta istical model for such interference which can be usd in the yqt,"design process. The need for RTCE is most pronounced for links involving mobil.,terminals since the nature, orientation, etc of the paths will change with time thusmaking off-line analysis more approximate.

To date, there has been considerable experimental work on il-trnativ,- RTCFtechniques, but relatively little has been published quantifying their benefits inrelation to systems making use of off-line data. One set of results (Darnell, 19781indicates that an improvement in circuit availability of the order of 45% c-an beachieved by simple error counting RTCF in comparison with 2-fr-qunoy operation;however, much more performance data is required for other algorithm;.

It would seem that dedicated RTCE systems such as ionospheric sounders, whichrequire expensive special-purpose equipment and cause significant spectralcongestion, will not find wide application in HF communications. Rather, RTCFprocedures which can be integrated into the communications system, will use the sam,basic equipment and will operate only in assigned channels appear to offer a morelogical and economic way forward. This may well place additional requirements uponthe equipment specified for fut ire HF communications in terms of control,flexibility, frequency agility. etc.

Bearing in mind the above comments, the techniques which currently appear tooffer the greatest promi!;e are:

(a) Simple error counting (Section 7,3).(b) Pilot tone phase error measurement (Sections 7.2 and 8.41.(c) Systems based upon the general CHEC principle (Section 7.1).(d) The use of auxiliary EDC processing in encrypted systems

(Section 8.4).P(e Passive monitoring of noise and interference characteristics(Sections 8.1 and 9).

(f; In-band RTCE within a nominal 3 kHz assigned channel(Section 8.1).

In the context of the overall HF communication system, RTCE data could, inprinciple, be employed as a source of control information to assist in the adaptationof the following parameters:

- Transmitter power level;- Frequency of operation;- Bandwidth;- Information rate;- EDC algorithm;- Modulation type and spectral format;- Start time and duration of transmission;- Antenna characteristics, eg null positions;- Diversity combining algorithm

etc.

10.2 Potential Advantages of RTCE

The potential advantages to the HF communicator arising from the use of RTCF canbe summarised as:

(a) Off-line propagation analysis requirements can be eliminatedfor operational purposes; however, this form of analysiswill still be valuable for system planning purposes.

(b) The effects of manmade interference can be measured andspecified quantitatively, thus eliminating the major causeof operational uncertainty.

(c) Relatively transient propagation modes, such as sporadic Elayer refraction, can be identified and used for highquality communication; the presence of these modes canincrease the available spectrum by as much as 2 or 3 times.

(d) RTCE facilitatms the selection of channels higher infrequency than would have been suggested by off-linepropagation analysis, hence reducing spectrum congestion.

(e) R'CE provides a means of automatically selecting an optimumtransmission channel and of ranking stand-by channels

0-lIII I I |IEI

in order of preference - an essenlial pre-requisite F.r an.automatic HF system.

(f) Radiated power can be minimis(-d, consistent with ,n-ing areceived signal fidelity criterion, thus reducing spectrilpollution.

(g) RTCE provides the basic data required for adaptation ofcommunication system parameters other than fr.quoncy, eqsignal processing algorithms, ant.?nna charact- ristics, etc.

11. REFERENCES

(I) Darnell, M., 1983, "HF system design principles", ACARDLecture Series 127 "Modern HF communications".

(2) Haydon, G W., et al, 1976, "Predicting the pertormanc. fhigh-frequency sky-wave telecommunication systems (the useof the HFMUFES 4 program", (IS Dept. of Commerce/Office ofTelecommunications, OT Report 76-102.

(3) Darnell, M., 1978, "Channel evaluation t,chniques fordispersive communications paths", in "Communications systemsand random process theory", ed. T.K.Skwirzynski, Sijthoff &Noordhoff, The %"' -rlands, 425-460.

(4) CCIR, 1981, "Rea -time channel -valua ion or ionosphe ricradio circuits", Provision,. report AK/6, October.

(5) Darnell, M., 1975, "2harn'-l e:tima:ion t-chniques for HFcommunications", AGARD CP-17; 'Paio syste-ms and theionosphere", Paper 16, Athens.

(6) Barker, R.H., 1953, "Group synchronising of hinary digitalsystems", in "Communic.ition theory", London, Butterworth,273-287.

(7) Coll, D.C. & Storey, J.R., 1964, "Ionospheric sounding usingcoded pulse signals", Rad S-i 7 of Research, Vol 69D(10),1155-1159.

(8) Mann, H.B.(Ed), 1968, "Error correcting codes", Wiley, 195-225.

(9) Probst, S.E., 1968, "The CURTS concept and current status ofdevelopment", in "Ionospheric radio communications", Plenum,370-379.

(10) Barry, G.H. & Fenwick, R.B., 1965, "Extra terrestrial andionospheric sounding with synthesised frequency sweeps",Hewlett-Packard J, Vol 16(11), 8-12.

(11) Stevens, E.E., 1968, "The CHFC sounding system", in"Ionospheric radio communications", Plenum, 359-369.

(12) Wynne, N., 1979, "Sea trial results for an experimental

channel estimation system", IEE Colloquium Digest 1979/48.

(13(Chow, S.R., et al, 1981, "Communications for smallcommunities in developing countries", PacificTelecommunications Conference, Honolulu, January 12-14.

(14) Betts, J.A. & Darnell, M., 1975, "Real-time HF channelestimation by phase measurements on low-level pilot tones",AGARD CP-173, "Radio systems and the ionospher", Paper 18,Athens.

(15) Awcock, R.W.J., 1968, "The LINCOMPEX system", Point-to-PointCommunications, July, 130-142.

(16) Leon, B.J., 1973, "Bit error rate amplification', NationalTelecommunications Conference, November.

(17) Darnell, M., 1979, "An HF data modem with in-band frequencyagility", IEE Coll,,I:ium Digest 1979/48.

(18) Gott, G.F. & Hillam, B., 1979, "The improvement of slow ratefak by frequency agility and coding", IEE Colloquium Digest1979/48.

(19) Mosler, R.R. & Clabaugh, R.G., 1958, "Kineplex, a bandwidthefficient transmission system*, Trans AIEE(Comm &Electronics), Vol 34, January, 723-727.

6-14

(20) Chase, D., 1973, "A combined coding and modulation approachfor communication over dispersive channels", IEEE Trans. VolCOM-21(3), 159-174.

(21) Cottrell, R.A., 1979, "An automatic HF channel monitoringsystem*, IEE Colloquium Digest 1979/48.

(22) Barry, G.H. & Fenwick, R.B., 1975, "Techniques for real-timeHP channel measurement and optimum data transmission", AGARnCP-173 "Radio systems and the ionosphere", Athens.

(23) Lee, Y.W., "Statistical theory of communication", Wiley,323-351

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INTRODUCTION TO CODING FOR HF COIUNICATIONS

byMario D. Crossi

Harvard-Smithsonian Center for AstrophysicsCambridge, Massachusetts

02138

U.S.A.

ABSTRACT

The increasing demand for reliable, low error-rate, high-speed digital data transmission at HF has crested the need for the adoption of coding schemes. As it is well appreciated by the practicing communicator,a problem in high-speed data transmission is the occurrence of errors. Codes provide an effective approachfor the reduction of the error rate. Linear block codes ( of which cyclic codes are a subclass) and convo-lutional codes are the main categories of codes of interest to HF communications. They are capable of cor-recting random errors due to white Gaussian noise, as well as burst errors due to impulse noise. In blockcodes, a block of information bits is followed insediately by a group of check bits. The latter verify thepresence of errors in the former. In convolutional codes, check bits are continuously interleaved ith iot-,rmarion bits, and they check the presence of errors not only in the block immediately preceeding them, butin other blocks as well. For the various coding schemes reviewed in the lecture, several numerical examplesare given , to help in the quantitative appraisal of the merits of a code, versus required equipment om-plexity,

A. INTRODUCTION

1. General

The first half of the twentieth century brought about the development ,f radio communic ati n, haracterized by the transmission of messages, speech and television that was mostly in analog form ( and with theHF ionospheric links figuring prominently in the handling of the intercontinental traffic). The se-,ond halthas seen an uninterrupted trend toward the digitization of tomunicat ions. with far reaching consequenesin terms of improved reliability, increased operational speed, reduced equipment size. freedo fr .ali-bration problems, improved ability to mechanize complicated signal processing algorithms etc. (l,1m-, lO,

[I- ;ieb anW-ia.17,2 sezncraft and Jacobs, 1965 [k] ;Gallager. ls [])

Digital cotmunications were given impetus by several driving needs. rost prominently by the ever cidering demand for data enchanges between computers and remote ter.inals. There is however. ax additical as-pect that has a great importance and that directly relates to the topic ,f this lecture : the abilit ,f

digital techniques t o make iL feas ible and pract ical to approach the theoret ical effic iency Icmit of a cr.-municat ion channel. It is here. in fact, that cod ing enters the pic tore, as an approach to opt ie-ze ,omu i -cations on a given channel (in our case, ionospheri HF channels) rather than a wan to achieve secrecy ivmilitary cosaunications.

In order to better illustrate the point above, we maist backtrack a few decades, and go back to the urkof Hartley in the late '20s, and to the publications of Shannon, Wiener, Fan, and other pioneers of digitalcommiunications, in the mid '40s. These authors, all of great theoretical strength, developed methods for thecomputation of the efficiency of a communications system, and established the theoretical maximum that, forevery type of system, this efficiency can attain. Shannon had the intuition that achieving error-free digit-al conmmications on noisv channels, and performing the most efficient ionversion of an analog signalilt,, coded digital form, were two facets of the same problem, having a common solution. Shannon's maivresult is actually that, as long as the input rate to a channel ev-:oder is less than a quantity called thechannel capacity C, encoding and decoding approaches do exist, that. asymptotically and for arbitrarilylong sequences. lead to the error-free recorstruction, at the receiving terminal of the li-k. Lf the inputsequence. The capacity C (bits/sec) can be easily computed from the receiver's bandwidth N (Hz) and fr-mthe Signal/Noise ratio (power ratio) S/N :

SC = W log (1 + -- )

2

What coding ultimately does is to maximize the likelihood of correct interpretation, at the receivingend of the link, of the incoming waveforms, and to push the data rate toward the theoretical limit ( esta-blished by Shannon.On the strength of these conceptual developents.a wealth of codes were developed, suchas the Shannon-Fano-Hoffmsn codes for a discrete channel, the Hamming codes for a discrete channel withdiscrete noise, the Bose-ChaudhurL-Hocquenghen codes, that have found use in HF military links and thatresulted from contributions due to Reed. Muller, Golay, Slepian. and others. For a channel with white GauseIan noise, the search for high-efficiency codes translated in the search for waveforms that exhibit thesmallest possible mutual correlation.

For several decades, the design of efficient codes was exclusively a theoretical exercise, with no opportunity to reach the stage of engineering implementation. Technology was not Yt on a par with the complicat-ed hardware that they required. However, recent advances in technology, especially the development of largescale, integrated-circuits building blocks, have changed all this. It finally became feasible and practicalto mechanize coders and decoders that are known from theoretical work to be optimum, and several implement&tions 'ave actually already entered the practice of HF communications. Figure 1 is a typical block diagramof a digital link between two terminals. Usually. the alphabet is binary ( coding in digits I and 0 ) andthe source may be a computer, whose output is transformed by the source encoder into a (Oinary) sequence of

ones and zeros. The transformation is done in such a way that the amount of bits/sec that represe:Its thesource output, is the minimum required by the source frequency content and by the number of disceritblelevels. Also the transformation is done in such a way that the reconstruction if the source output at terminal B is feasible and adheres to its original. The channel encoder ( as well as the de-der in e epi,,lis the must important unit from the standpoint of the topic of this lecture: its function is t,, transforrmthe binary data sequence at the output of the source encoder into some longer sequence that is called thecode word. This longer sequence enters then a modulator ( to modulate for instance bv FSK. or FrequencyShift Keying, a radio carrier).The block called channel is the medium where the signals propagate. in ourcase an ionospheric path at HF ; while in the channel, the signals are corrupted iy noise and it terference.

At terminal B, the demodulator makes the decision whether, for every received signal, the transmittedwaveform was a 1 or a 0. The channel-decoder, then, by knowing the rules by which the channel encoder didoperate, attempts to correct the transmission errors and performs an estimate of the actual code word thatwas transmitted. The source decoder transforms this code word, that has been reduced to a stream of informstion bits, into an estimation of the actual source output, nod delivers it to the user. If the channel ischaracterized by low noise, the various estimations performed by the units of terminal B will be very simi-lar to the functions that they are meant to represent. If the channel, on the contrary, is very noisy, sub-stantial differences may arise ( Lin, 1970 , [3] ).

tn Figure 1, the channel encoder and the channel decoder perform the function of error control. This isdone through a judicious use of redundancy (Shanmugan, 1979, [.J . The channel encoder adds digits t, thebit stream of the source's message. While these additional bits do not convey information in themselves.they make it possible for the channel decoder to detect and correct errors in the received, information-heating,bit stream, thus reducing the probability of errors. The encoder divides the input message bitsinto blocks of k message bits, and replaces each k bit message block with an n bit codeword by adding n-kcheck bits to each message block. The decoder looks at the received version of the original code word. whichmay occasionally contain errors, and attempts to decode the k message bits. The design of the encodtr anddecoder consists of selecting rules for generating code words from message blocks and for extracting messageblocks from the received version of the codewords, with the fundamental aim of lowering the overall pr,,ba-bility of error.

2. Examples of code generation

In order to start with a simple example, let's consider a block with five horizontal lines ( or rows)and with seven vertical columns This block ( with n = 5 x 7 = 35 ) represents schematically the word "Hello"in the teletype 7-unit alphabet :

H 00tLOlle 01000011 0010011I OO0Ol1o 0000111

A code word, aimed at reducing the probabilliL of errors in the transmission of the block above, can begenerated as follows : we add to each line and to each column one more symbol, in order to make the overallnumber of Is even in each line and in each column. At the end, we add a symbol at the lower right corner.tomake even the number of Is contained in the last line. The new block is as follows

0001011 10100001 00010011 10010011 10000111 1010110 0

If during the transmission process an error occurrs, this can be corrected, provided that there is onlvone of them. Correction is done by checking each line and each column for even parity ( an even number ofIs). If there is a single error, one column-check and one line-check will fail, and the error wilP be identified at the intersection and will be corrected. The 48 symbols of the block above form a code word.This code has a total n = 48 symbols, of which k = 35 symbols are information-carrying symbols. -c is re-ferred to as a (48, 35) code. There are n-k = 48 - 35 = 13 check symbols. These are the redundant digitsadded to the message in order to provide the code word with error-correcting capability.

All the codes illustrated in this lecture are based on ideas similar to the principle that allowed usto generate the code word (48, 35 ) above. The mathematics involved might be of higher caliber, the codesmight be more efficient. However, there is a striking fundamental similarity between the simple code intro-duced above and the more sophisticated ones that we wilL illustrate later-on in this" lecture.

Let's see now another example that shows how the probability of error is reduced by the adoption of acoding scheme. Let's assume that we have a HF link with a bandwidth of 3 Kfz and a Signal-to-Noise ratioof 13 dB ( power ratio -620). We want to transmit a data rate (from the source).of 1200 bitslsec, with anerror rate less than 10- . We have available a modem that can operate at the rates of 1220, 2400, J600,4800, and 6000 bts/sec, with error probabilities respectively of 2 l0

"-, 4 10

", 8 i0 , 1.4 10' end

2.4 10"3. According to the Shannon theorem, the channel capacity C is, in our asse :

C - W lo 2 ( 1 + S/N ) 3 KHz lg 2 ( I + 20 ) 3 Kbits/sec.

e

Therefore, since the source bit rate is less than the channel capacity C, we should be able to find a wavto transmit the data with an infinitesimally small probability of error. Let's start considering a codeobtained simply by tripling the symbols that come out fr,,m the source encoder: if it is a i). we use 0001;if it is a 1, we use 111. These are now our codewords. We adopt in reception a logic based on ma orito ruling : an error occurs when in a word two or more symbols are wrong. The data rate that we must use iv themodem is 3600 bits/sec, with corresponding error rate 8 l0-

4. The codeword is thus characterized '-v the

following error probability

P ( that two or more bits in the triplet are in error = c (

e -43where qc = 8 10

", if we signal at the rate in the modem of 3s00 bits/se. Numerically, the equat ion abve

yields: -b -6Pe = 1.9 10 -> 10"6 ( 10 is the required error rate, not to be exceeded).

The results above are therefore not acceptable and we must try a longer -ods-ord. in order to fulfillthe error rate requirement. Let's generate in the modem the codeword 00000 for every 0 at the source's out-put, and 11111 for every 1. Now the modem operates at the rate of 6000 bits/sec I five times the 1200 bts'sec rate of the source) and q = 2.4 10

-3. We still use the majority rule logic : an error will cc urr in

reception when three or more Symbols are received wrong. The error probability P is nowe

P( that three or more bits in the quintuplet are in error) =-c5I-= 1.376 0

t7 lO

"5

= ) c( "qc) 4,)q (l q,) + 5 c 1.7107 o6

With the quintuplet we meet therefore the error rate requirement.

3. Error detection and error correction approaches

In the examples given in Section 2, we adopted an approach that corrects as bent as feasible. threceived errors, caused by noise. This approach belongs to the category .,f forward-error-correcting codes.There is another category of approaches that perfortsin reception the error detection ( detection only. notinclusive of correction) and in which the terminal B in Figure 1 retransmits back to terminal A the receivedmessage, once that an error has been detected, for a repetition of the exchange. There are some obvious in-conveniences associated with this method : we must have a two-way link between the two terminals, we mustuse time for message retransmission, we must send from B to A an acknowledgement even when the messagereceived at B appears correct, etc. However, there is the great advantage that the overall probability oferror is now much lower than achievable with the forward-error-correcting codes. We can easily see howthis happens with the following example. Let's assume that the receiver/decoder accepts only ( if thetriplets of the example in Section 2 are adopted) a 0 when what is received is 000, and a 1, only when Illis received. In any other case, terminal B requests from A a retransmission. An error now occurrs only ifall three bits of the triplet are wrong. We have therefore for P :

P ( that all three bits are wrong) = ( q )3 = 5.12 101in< 0«10,

e c

In fact, because the modem now works at 3600 bits/sec, we know that q = 8 lt- .

Therefore, we do not needin this case to use any quintuplet in order to satisfy the overall error probability requirement.

4. Random errors and burst errors, and their control by codir.g

Generally, two types of noise are encountered In comrmunication channels. The first kind is Gaussiannoise, including thermal noise in the equipment, cosmic noise, etc. This noise is often white. In the caseof white Gaussian noise, the occurrence of errors during a particular signaling interval, does not affectthe performance of the communication system during the subsequeot signaling interval. The discrete channelin this case can be modeled by a binary symmetric channel and the errors due to white Gaussian noise arereferred to as random errors ( Shanmugan~lq3[4]).A second type of noise often encountered in a communicationchannel is the impulse noise, where high intensity noise bursts sporadically appear during long quiet periods.When this happen, several bits in sequence may be affected, and errors occur in bursts.

There are error control schemes that are particularly effective in counteracting random errors. Otherschemes have special imunity from burst errors. Error correcting codes are divided in two general catego-ries: block codes ( of which a subclass are the cyclic codes) ana convolutional codes. In block codes, ablock of information bits is followed by a group of check bits that are derived from the former. At thereceiving terminal, the check bits are used to verify the information bits in the block immediately preceedIng the check bits. In convolutional codes, check bits are conttnously interleaved with information bits.not only in the block immediately preceeding them, but In other blocks as well. The cyclic codes have particular advantages, in as much as they simplify considerably the required encoding and decoding equipment.

B. LINEAR BLOCK CODES(*)

1. The fundamental conceptWe will now illustrate the block codes, in which each block of k message bits is encoded into a block

(*) This section paraphrases Sharmugan (1979), [4]. Section 9.2, by permission, gratefully acknowledged, ofthe Publisher John Wiley & Sons.

-4

n>k bits. by adding n-k check bits derived from, the k message bits They are called linear wheneach if the codewords ( n bit block at the 'utput .f the channel enc.slerl can be expressed as a linearcombination of k linearly independent ,.de ,et ,rs : liiea: hi ,k codes are the m.st comonly used blockcdes and we will limit our discussion t, them. In all the operati ,s pertaining the generation of these,odes, we must remember to use modulo 2 arithmeti- This is how this arithrsetit works: we make additionsthe regular way ( for instance, 1 + 1 = 2 ). However. 4e divide then the result by 2 and we take the rnmai:nder as the final result of the modulo 2 ,peration For instance. fr the 1 + 1 = 2 .ase. we divide 2 by 2.the remainder is zero. and therefore we write I + I = 0 If we or 0 + 1. and 'e divide the result by 2.the remainder ,f the regular division is I and thus we ...... !de ' - I = I.

Let s see some examples of code generation An effectiv- av ,f impleseting this generation is theuse of matrix representation: C = DG. where D is the message ve, tir. ( the final ,deword and G is theso-called generator matrix, that embodies the rules ad oted fr detecti-g error, the received codeword.The generator matrix has dimensions kxn . and has the tLrm:

, = [k ] kss

where I is the identity matrix of order k. P is an arbitrary matrix *f dimensions kx(n-k). This last ma-trix, nce chosen, fully defines the In.k) block code completely Suppose that the generator matrix C ,fa (6,3) block code is

F1o0 o 1 11G = '0I 0 l )'

0 1 1J

and we want to find all code sectors ,f this code. The message block size for this code is 3 and the overalllength of the ,ode vetoirs is n = 6. The possible 8 messages are : l0.0.0). (0..1). (0.1.0), (0.1.1 ll(..0.(1,1,0), ( 1.1.1). (1,0.1). The code vector for the message blok D (111) is:

0 0 0 11

C = 01=(lll) ) 0 ( 1 ) 00 )0110

The encoder has to store the G matrix (or at the very least, the submatrix P of G) and must perform binaryarithmetic operations to generate the check bits. Associated with each (,k) block code. there is a paritycheck matrix It which is defined as

H P:n-kj (n-k)n

Twhere P is the transpose of the matrix P. The transpose is obtained from the original matrix by changingplace of each element of the matrix, following the rule that an element p.. goes to the place p.' In thisway. if the original matrix has. for example. 7 lines and 5 columns, its 'transpose will have 5 lines and7 columns.

Let's see now another example of codeword generation. We want to encode an 11 bit data sequence into'a (15,11) code word. This ccde is fully specified by the related 1l-by-15 generator matrix. This could bethe matrix here below:

0000000000 100100100000000 110100l00000000 0111

r 00010000000 1110

00000100000 o 110000000l0000 01010000000l000 101100000000100 10000000000010 0110O0000000001 0011

In this matrix, the llxll part is just the identity mrrix of ord ilI. The second part is totally arbitrary,as already indicated. Encoding the data sequence D = 100001101 gives: C-DG =[0OOlOOlO 0011] . Notethat the first 11 hits of C are identical to D and that the last 4 bits of C are the sums of the bits of Dspecified by the last four columns of G. For example, the first parity bit is the sum of the first, second.third, fourth, sixth, eight, ninth bits of D. that is 1+0+0+0+0+1+0 =0. In an equivalent way. C can bethought of as the sum of the rows of G which correspond to ones in P. Thus, in the example, C is the sum,f the first, fifth, eight, and tenth rows of G.

As defined, a code word in a systematic linear code is an s-tuple with the property that the n ksubsets of the k information bits of the word specified by the rightmost n-k colums of the generator matrixadd to the corresponding parity check bit.

Let's see now how at the receiving terminal, the decoder utilizes the parity check matrix H. Thismatrix Is used to verify whether a codeword C is generated by the matrix G - rI PJ . This verificationcan be done as follows. C is a codeword in the (n.k) block code generated by T kif and anly if CHT-O.where

e

II is the transpae of tie matrix H. If C is a code vector transmitted over a oisy channel and R is thereceived vet¢tor, we have that R is the sum of the original code vector C and of an error vector E. Thereceiver does not know C and F and its funct ion is to obtain C from R and the message block D from C. Thereceiver perform its function by determining a (n-k) vector S defined as

S - R HT

.

This vector is called the error syndrome of R, and we can write for it t S = CH T + E"T = Eli because Cli 3.

thus the sydroce of a received sect,or is zero if R is a valid code vector. Furthermore. S is related tothe error vector E and the decoder uses S to detect and correct errors. As an example. let's consider a(7,4) block code generated by

1 00o I1 IG = o 1 0 011

00 0 10 1 j

The paritvcheck matrix 1i for this code is:

H J1010!

TP 13pi

For a message block D = (1011), the code vector C is given by C = DG = (1 0 1 1 0 0 1 ), and the syndromeS is S = CIT

= (000). Now, if the third bit of the code vector C suffered an error in transmission, then

the received vector R will be :R = ( 1 0 0 1 0 0 1) = ( 1 0 1 1 0 0 1 ) + ( 0 0 1 0 0 0 0) = C + E. andthe syndrome of R is S = RHT (101) = EHIT. where E is the error vector (0 0 1 0 0 0 0). Note that thesyndrome S for an error in the third bit is the third row of the HT matrix. It can be verified that, for

this code, a single error in the ith bit of C would lead to a syndrome vector that would be identical tothe ith row of the matrix IVt. Thus single errors can be corrected at the receiver by comparing S with therows of HT and correcting the ith received bit if S matches with the 1th row of HT.'This simple scheme doesnot work if multiple errors occur.

2. Terminology and basic properties

In defining the error correction capability of a linear block code. sosne new terminology is utiliz-ed. such as the weigth of a code and its minimum distance. The weight of a code is defined as the numberof non-zero components in the codeword, The distance between two code vectors is the number of the comp

0-

vents in which they differ, while the minimum distance of a block code is the smallest distance betweenany pair of codewords in the code. An Important property to remember is that the minimum distance of a block

code is equal to the minimum weight of any no-zero word in the code. An example will clarify these points.Let's conrsider the (6,3) block code introduced in the previous section. Table I here below gives the weightof the various codewords. From the second column in Table I. we see that the minimum distance is 3. No two

codewords in this code differ in less than three places. The ability of a linear block code to correct random

TABLE I

Codewords Weight

Codeword Weight

000000 0001110) 3010101 3011011 4100011 3101101 4110110 4111000 3

errors can be specified in terms of the code's minimum distance. The decoder will associate a received vectorR with a transmitted code vector C if C is the code vector closest to R in the sense of the Hamming distance.

Another property to remember is that a linear block code with a minimum distance dmin can correct up to

[dm I-)/2J errors and detect up to dm -1 errors In each codeword. where L( dm in I )/2ldenotes thelargest integer no greater than (drin " 1)02. If we call t the errors that the code will correct, we have

t KC.d mi n"

A

We can also show that such a code can detect up to d - 1 errors. We can deduce from the above that fora given n and k, we should design a (n,k) code witRWininimum distance as large as possible.

3. Hamming Codes

From the equation just written, it follows that linear block codes capable of correcting single errorsmust have d _,. 3. Such codes are easy to construct. Each row in H

T has (nk) entries, and each entry can

b ither am or a 1. We have therefore 2

n-k distinct rows of (n-k) entries, out of which we can select

distint rows of HT ( the row of O's is the only one that we cannot use). Since the matrix H hasn rows, for all of them to be distinct, we need: 2

n -1 n. In other words, the number of parity bits

in this (nk) code satisfies the inequality (n-k) log, (n+l). So. given a message size k . we can deter-mine the minimum size n for the codewords from n.k og2 ( n + 1), where n has to be an integer.

Assume that we have to design a linear block code with a minimum distance of three and a message blocksize of eight bits. We proceed this way : from the inequality above we have n*8 + log2 (n+l). The smallest value of n that satisfies this condition is n = 12. Thus we need a (12.8) block code. The transposeof the parity cheLk matrix H will have a size 12 by 4. The first 8 rows are arbitrarily chosen with therestrictions that no row is identically zero,. and all rows are distinct. A possible choice for H is:

F 1000110001110011010

T 0101

100001000100001

The generator matrix is:

F10000000 110010100000 00110i0010000 1001

11; oooo o,0

0000000 0110

000 00101

0j00 0 0 1 0 0

010J

00000001 0L11

The receiver forms the syndrome S = HIand accepts the received code vector if 50-. Stoxlv errors are alcavsorrec ted; double erroirs an he detected but c annot he corrected; multiple errors will result in general.then incorrect detodinig. The efficiency of block codes with minimum distance three (Hamming Codes) improves asthmessage block size is increased. We can verify that for k-64, a minimum distance three code with effi-ciency 0.90 does exist, and that for k=256, a code with efficiency 0.97 can be found.

We have seen in the above that the decoding operation consists in finding a codeword C. that is theclosest to the received word R. This require s storing 2k codewords and comparing R with eacA of them. Sinceeach codeword is of length n, the storage required contains n2k bits. Eves for modest size of k and n.the storage requirement is excessive, and the processing requirement also becomes soon imprac..scal.There is ,however, a way of reducing considerably both these requirements, as we wsill see nest. in Secr,.o4.

4. Table lookup and standard array

We will consider now a decoding scheme (table lookout) that requires the storage of 2 -k syndromeS vectors of length n-k bits and the

2n-11 n-bit error patterns corresponding to these syndromes. Thus..

the storage required will he 2n-kx (2n - k) bits. For high-efficiency codes, 2n-k "m n; hence, the storagerequired will be of the order of n 2n-kbits, a much smaller capacity' thban nkbits required if the tablelook-out approach is not used. Even with this reduction, though, the decoding scheme of block (odes maohe impractical. Pot instance, for a (200,175) code, the storage requirement is of 7.b Gigabits!!

The table look-out approach works in the following way. Suppose that a (nhk) linear code is used forerror correcting purposes. Let C1 1 CI .... I C~ ij e the code vectors of C. If g is the received vector, itcan be any one of the 2 k n-tuples t~at are vaT id c.'dewords. The decoder can perform the task of associatingg with one of the n-tuples, by partitioning the set of 2n n-tuples as shown in Table 11. The code vectors

TABLE t1Example of standard arrayfor a (nk) linear block

codeU tk;

2 9 ....... C

2k

E 2 C2+E 2 C 3 + E 2 . ... C2k +E2

E 3 C 2+E 3 C 3 + E .** *C 2k+E 3

E2n_ k ot+E 2l.k C3+E2nk.C 2k+ E2 n-

C C 2...2 are placed in the first row, with the code vector of all zeros appearing in the leftmostI ' 2'" 2 k n kposition.The first element in the second row E is any one of (2 - 2 ) n-tuples not appearing in the firstrow. Once E2 is chosen, the second row is completed by adding E2 to the codewords, as shown in Table II.

Once that the second row has been completed, an unused n-tuple E3 is chosen to begin the third row and the

sum of C +E ( with i=1,2, ...2 k) are placed in the third row. The process is continued until all the 2"

i 3n-tuples are used. The resulting array is called the standard array for the code and it consists of 2kcoumnsthat are disjoint. Each column has 2 nk n-tuples with the topmost n-tuple as a code vector. The ith column

is the partition T. that will be used for decoding. The rows of the standard array are called co-sets and

the first element In each row in called a co-set leader. The standard array has the property that each ele-ment is distinct and hence the columns are disjoint; furthermore, if the error pattern coincides with aco-set leader, the received error is correctly decoded. If it does not, then an incorrect decoding willresult. Thus the co-set leaders are called correctable error patterns.

tn order to minimize the probability of incorrect decoding, the 2n - k

o-set leaders are ch,,sen to bethe error patterns that are most likely to occur for a given channel. If E and Ej are t-o error patternswith weights Wi and W., then for a channel in which only random errors ar occurring, E i is more likely to

occur than E. if Wi > W . Therefore. when constructing a standard array, the co-set leader should be those:,

as the vector with minimum weight from the remaining available vectors. A standard array has an importantproperty that leads to a simpler decoding process : all the 2k n-tuples of a co-set have the same syndromeand the syndromes of different to-sets are different. The one-t'-one correspondence between a co-set leader(correctable error pattern) and a syndrome leads to )he following procedure for decoding: a) c,.npute thesyndrome RHT for the received vector R. Let RHT= S. ; b) locate the co-set I ader Ei that has a svndrome

EiHT =

S. Then, Ei is assumed to be the error pattern caused bv the noisy channel: C) the code vector C is

obtained from R by C = R + E.. Since the most probable error patterns have been chosen as the c-set leaders,

this scheme will correct the2n0k most likely error patterns introduced by the channel.

C. CYCLIC CODES (*)

The research conducted on linear block codes has identified a subclass of these codes. callcd thecyclic codes, that haveispecially attractive properties, such as ease of implementation; ability to cocrectlarge numbers of random errors, long burst of errors and loss of synchronization; etc. These codes have amathematical structure that helps considerably in the design of error-correction features and furthermore.due to their cyclic nature, require encoding/decoding equipment that is considerably simpler than requiredby regular block codes. A cyclic (n,k) code has the property that every cyclic shift of a code word is an-other code word. That is, if

C = C C ........ C

is a code word, so are 0

[Cn-2, Cn-i........... Ha ef n

Example for n-3

(CO I c1 ]This formulation of cyclic codes suggests treating the elements of each code word as coefficient of

a polynomial of degree n-l. With this convention, the codeword C can be represented with the polynomial

C()- Cn2 xnC 2n - + Cl x

+ CO"

The condition that every cyclic shift of a code word be another code word can be expressed as follows. ThatC(x) is a code word implies that xiC(x) modulo-(xn+l) is also a code word for all i. It can be verified that

multiplication by x-modulo-(xn4l) results in a cyclic shift and that the coefficients of x'C(x)-modulo-(xn+l)

are, in fact.

[Cn.i C- .C 2 . CI I C0 , Cn. l .. Cn-]

Several interesting properties of the generator matrix of a cyclic code can be deduced from theabove definition. We will illustrate them by via of an example, considering again the (15,11) code Introduced in section B.1. This code is a cyclic code and its generator matrix, written in polynomial form, is asfollows:

(*) This Section paraphrases Lucky at al. (1968) , Section 10.2.4, by permission, gratefully acknowledged,of the Publisher McGraw-Hill Book Co.

Is 4 5

0,2 i - - •,. c 2- s is

G =[l!PJ= II , = 1' :

kx2 .'2

5'51 2

4where g(x) = s +x+l. Encoding a k-bit data block by multiplying it by the generator matrix G is equivalent

to the following polynomial operation.The polynomial representation of the information block, denoted by

d(x) has a degree less than k; therefore .n-kd(x) has a degree less than n. Also

xn k d O ) q(x) + r(x)

g(x) g(-)

where q(x) has a degree less than k and r(x) has a degree less than a-k. which is the degree of g(x). Thus,

the polynomial n-kd(x) + r(x) is divisible by g(x) and is a codeword in the code generated by g(x). Thisword consists of unaltered k-bit information block followed by n-k linear combinations of the information

bits. It must be identical to the word formed by multiplying the k-place vector D by the matrix G since, aswe have seen, there is only one code polynomial of degree n-k in a cyclic (npk) code. The syndrome associat

ed with a given n-tuple can be calculated in a similar manner. Let e(x) =e dx) +e p<) be the polynomial re-

presentation of such n-tuple. The syndrome is obtained by encoding the information section of the n-tuple

and by adding the resulting check bits to the corresponding bits of the parity section of the n-tuple. That

is, the syndrome s(x) is given by s(x) = e (x) + r(x). where r(x) is the remainder obtained by dividingP

ed(x) by g(x). Since e (x) has a degree less than g(x), this is identical to the remainder obtained by divid

ing e(x) = ed(x) + ep (x) by g(x). Since g(x) divides every code word c(s), the syndrome is identical to that

of e(x)+ c(x). Encoding and syndrome calculation can be mechanized in a remarkably simple manner.

D, CONVOLUTIONAL CODES(*)

1. General properties

While in the block codes, a block of n digits depends on the block of the related k input message d.-gits. in a convolutional code, the block of n digits generated by the encoder in a certain time unit depends

not only on the block of k message digits within that time unit, but also on the preceding (N-1) blocks of

message digits (NNI). Usually the values of n and k are small. Like block codes.connolutional codes can bedesigned to either detect or correct errors. In practice, they are used mostly for error correction. The ana-lysis of their performance is complicated and is normally done by simulating the encoding and the decodingoperations in a digital computer.

In the following sections we will give an introductory level treatment of the convolutional codes, adwe will illustrate both the encoding operation and some of the decoding approaches.

2. The encoding operation

The code generated by a convolutional encoder is called a (n,k) convolutional code of constraint lengthnN digits and efficiency k/n. The parameters of the encoder, k, N, and n are in general small integers andthe encoder consists of shift registers and modulo-2 adders. An encoder for a (3.1) convolutional code with

a constraint length of nine bits is shown in Figure 2. The operation of the encoder proceeds as followsWe assume that the shift register is initially clear. The first bit of the input data is entered into D .

During this message bit interval, the commutator samples the modulo-2 adder outputs c l,c2 and c 3 Thus, a

single message bit yields three output bits. The next message bit in the input sequence now enters D1, while

the content of DI is shifted into D2

and the commutator again samples the three adder outputs. The process

is repeated until the last message bit Is shifted into D3. It is important to notice that the convolutional

encoder operates on the message stream in a contimUous manner. thus it requires very little buffering and

storage. Another important point is that each message bit has its influence on Nxn digits, where N is the

size of the shift register, and n is the number of the commutator segments.

3. The decoding operation

It helps~in understanding the decoding operationto make use of the code tree shown in Figure 3, whichapplies to the convolutional encoder shown in Figure 2. The starting point of the code tree is at left and

(*) This section paraphrases Shanmugan (1979), [4] . Section 9.6. by permission, gratefully acknowledged,

of the Publisher John Wiley & Sons.

it corresponds to the situation before the occurrence of the ith message bit d.. We assume that the messagebits dI., and d are cero. The paths shown in the code tree are generated by using the rule that we shall

iI i-2diverge upward from a node of the tree when the input bit is 0. The starting node (A) corresponds to di-lq0 and d =0. Toen. if d.=O. we move upward from the initial node and the coder output is 000. Nodes 1.2.I and 4'iA be considered'as starting nodes for d i+2 with d.d = 00, 01, 10. and 11 respectively. For anyc-hZi-I-

given starting node, the first message bit influences the code blocks generated from the starting node andthe two succeediig nodes. Thus each message bit will have an effect on nine code digits and there are eightdistinct 9-hit code blocks associated with each starting node.

The code tree can be used as follows in a decoding operation called the exhaustive tree-search methodof dec-ding. In the absence of noise, the codewords will be received as transmitted. In this case, it issimple matter to reconstruct the transmitted bit sequence. We simply follow the codeword through the codetree n bits at a time ( n=3 for the example considered here). The transmitted message is then reconstructedfrom the path taken through the tree. The presence of noise introduces tranmsission errors; in this case thefollowing procedure can be used for reconstructing the transmitted codeword. Consider the ith message digitd i that has an influence on nN bits in the codeword. For the example shown in Figures 2. 3 and 4. N=3 and

n=3, so that d. has an effect on nine code digits. Hence. in order to deduce d i , there is no point in exa-

mining the codeword beyond the nine-digit block that has been influenced by d i . Onl the other hand, we w,,uldlose some of the benefits of the code, if we would use less than nine bits of the received codeword.If weassume that d, 1 and di-2 have been correctly decoded, then a starting node is defined on the code tree.

and we can identify eight distinct and valid 9-bit code blocks that emerge from this node. We compare the9-hit received code block we are examining with the eight valid code blocks, and discover the valid codeblock closest to the received code block ( closest in Hiamming distance). If this valid code bLock correspondsto an upward path from the starting node on the code tree, then d. is decoded as 0; otherwise, it is decodedas 1. After d is decoded, we use the decoded values of di_, and' d i to define a start ing node for decodiog

di+ 1 . This procedure is repeated until the etire message sequence is decoded.

The exhaustive tree-search method of decoding convolutional codes, briefl%, illustrated above, becomesimpractical as N bermes large, since the decoder has to examine 2 N branch sections of the code tree. An-ither decoding scheme avoids this lengthy process : it is called the Sequential Decoding Scheme. In sequen1tial decoding, at the arrival of a n-bit code block, the encoder compares these bits with the code blocksassociated with the two branches diverging from the starting node. The encoder follows an upward or down-ward path ( hence it decodes a message bit as 0 or 1. respectively) in the code tree, depending on whichof the code blocks exhibit the fewest discrepancies with the received bits.

If a received code block contains transmission errors, then the decoder might make an error and startout ,i a wrong path in the code tree. In such a case, the entire continuation of the path taken b% the enco-der will be in error. If the decoder keeps a running record of the total number of discrepancies between thereceived code bits and the code bits encountered along its path, then the likelihood is great that. afterhaving made the wrong turn at some node, the total number of errors will grow more rapidly than in the casethat the decoder follows the correct path. The decoder can be programmed to respond to such situations byretracine its path to the node at which an apparent error has been made, and then taking an alternate branchout of that node. In this way, the decoder will eventually find a path through N nodes. When such a path isfound, the decoder decides about the first message bit. Similarly. the second message bit is then determin-ed on the basis of the path searched out by the decoder, again N branches long.

The decoder begins retracing when the number of accumulated errors exceeds a threshold, as shown inFigure 4. Since every branch in the codetree is associated with n bits, then, on the average over a longpath of i branches, we can expect the total number of bit differences between the decoder path and the cor-responding received bit sequence to be (P)(n)(j) even when the correct path is being followed. The numberof bit errors accumulated will oscillate about E(j) (see Figure 4). if the encoder is following the correctpath ( path I in Figure 4). The accumulated bit error will, on the contrary, diverge sharply from E(j) soonafter a wrong decoder decision ( see path 2 in Figure 4). When the accumulated errors exceed a discard level( see Figure 4), the decoder decides that an error has been made and retraces its path to the nearest un-explored path and start moving forward again. After some trial and error, an entire N node section of thecode tree is retraced and at this point a decision is made about the message bit associated with this N no-de section. Thus, the sequential decoder operates on short code blocks most of the time, and reverts totrial and error search over long code blocks only when it ludges that an error has been made.

4. Recapitulation ,f the properties of convolutional codes

Although the theory of convolutional codes is not as well developed as that of block codes. severalpractical convolutional encoders/decoders have been built, for use in various applications. Convolutionalcodes have many of the basic properties of block codes : a) they can be encoded using simple shift registersand modulo-2 adders; b) while decoding is difficult, sevecal classes of codes have been found for which theamount of equipment required for decoding is not excessive; c) practical convolutional codes exist that arecapable of correcting random and burst types of errors. Their advantages over the block codes are several:1. since they operate on smaller blocks of data, the decoding delay is small; 2, smaller amount of storagehardware is required; 3. loss of synchronization is not as serious a problem as with block codes. In summary,convolutional codes, thiugh not as well developed and more difficult to analyze than block codes, are compe-titive with block codes in many applications.

.

7-1O

E. GETTING CLOSER TO THE ENGINEERING ASPECTS OF CODING (*)

We will illustrate in this section the mechanization of some of the coding schemes discussed in thecourse of the Lecture. We will specialize our treatment to the encoding of cyclic codes, touching base alsowith syndrome calculation, error detection, and error correction. Some mathematics is still here. but equip-ment block diagrams make their appearance.

We recapitulate that encoding consists of appending a set of parity checks to the data block beforetransmission; that the syndrome is simply the modulo-2 sum of these checks after transmission and the checkbits calculated on the received data block at the decoder; that error detection consists of determiningwhether or not the syndrome is the all-zero (n-k)-tuple ( if it is not. errors have occurred); that theseerrors can usually be corrc.ted by adding to the received word the error pattern associated with the syn-drome; that this association of error pattern with syndrome is essentially the decoding operation.

As an example of encoding mechanization, let's consider again the equation that was introduced inSection C:

n-kx d(x) r(x)

q(x) +g(x) g(x)

where g(x) denotes the generator polynomial of the code and xn-kd(x) + r(x) is the n-bit cylic codewordinto which a k-bit data block d(x) has to be encoded. Since the data bits are transmitted without altera-tion, encoding consists simply of determining r(x). The necessary division can be performed with the Lir-cuit in Figure 5. In the Fiure, the meaning of the symbols is as follows : l)-o-denotes a single binary

shift register stage ; 2) denotes an EXCLUSIVE -OR circ- or modulo-2 adder; 3).fsimply denotes

a connection, or the lack of one, depending on whether f. is I or 0, respectively.

Encoding is accomplished as follows: the data polynomial d(x) is shifted into the feedback shiftregister, as shown in Figure 5. After n-k shifts, the register contains the n-k high-order terms of

xn'kd(x). After the last data bit has been fed into the register, the feedback connection is broken, bymoving the switch from position D (data) to position P (party). and the content of the register is shift-ed to the channel. That this circuit actually divides x d(x) by g(x) to produce the (n-k)-bit remain-der r(x)jcan be seen by considering the following example. Let's use again the (15.11) code already intro-ded in thi Letue Th = 4 +x+

duced in this Lecture. Th generator polynomial of this code is g(x) = + ' + 1. Suppose that the datapolynomial d(x) = xlo+ x6 + x

3 + x is to be encoded. The remainder r(x) can be obtained by dividing x d(x)

by g(0). Thus:

14 II .7

5'4- I - 14 ' l1 1 T .0 -

I 7

1

11 17

Let's consider now the encoder for this code, shown on Figure 6. The first four shifts merely serveto load the first four terms of the dividend into the register. Table III shows the contents of the regis-ter as the encoding process is performed. Also shown are the dividends in the above division which corre-spond to the register contents at various stages of the encoding process.

TABLE III

Comparison of Register Contents & Dividends

o 55' lil 1,1 ..o 1

()This Sertion paraphrasea Lucky et al. , (1968). C'] Section 11.1 .by permission, gratefully acknow-[edged, of the Publisher McGraw-Hlll Book Co.

After the first four shifts, the four high-order bits of x4 d(x) occupy the register. On the nextshift, a I, corresponding to the quotient term x

lO . is emitted. Thus Is are added into the stages follo-

ing the feedback connections, and the register contents then correspond to the new dividend. obtained b.adding x

0g(x) to the first dividend. The key point is that when the register output is 1. the divide,d

is modified exactly as in the division process; likewise when it is 0, nothing is done in either case

Since the first n-k shifts serve only to load the register, the encoder of Figure 5 (a) can bemodified into the configuration of Figure 5 (b). In the latter figure, those load shifts are not necessar.The feedback information, which is simply the sum of the high-order bit of the dividend and the variouspast multiples of g(x), is thetsame in either case. The contents of the register differ until after the nshift of Figure 5 (a) ( the k shift of Figure 5 (b) ). At that time, the dividend has been shifted coi-pletely through the encoder, and thus both registers contain r(x).

Because it requires n-k fewer shifts, the circuit of Figure 5 (b) is usually preferable t. that ofFigure 5 (a) for encoding serial data. Encoding is performed here by shifting the data scque.nce simultaneously into the register and onto the line. After the last data bit has been shifted out. the switch is thrownfrom D to P, and the n-k parity bits are shifted out. This leaves the register empty and ready to a-eptthe first data bit of the next word, immedately.

Syndrome calculation differs from encoding only in that the received parity bits must be added to thechecks calculated on the received data. The circuit of Figure 5 (a) performs this addition autosaticallsvif

the received parity bits are shifted in immediately after the data. The circuit in Figure 6 oselds the sameresult : that is, the output is the syndrome.

Concerning the error detecti vi, this function can he implemented simply by adding a flip-flop to theoutput of the syndrome generator. If one or more Is appear in the syndrome, the flip-flop sets and an errorhas bben detected; otherwise, the reLeived n-tuple is a code word. Error corre~tior is simply an ass-iatio-nof a syndrome with an error pattern. This association can be visualized conveniently terms f the stan-dard array. A given code has exactly 2,

- k distinct co-sets. including the code itself. -sly one error

pattern in each co-set is correctable. Thus. by choosing the most probable error pattern in each co-set asthe co-set leader, the probability of erroneous decosdlng is minimized.

F. CODING APPLICATIONS TO HF COMINICATIONS

Most of the coding applications to HF coemunications have consisted thus far of error detecti-,n thr ughthe use of parity checks, and of autormatic error correction by retransmission (ARQ). Forward err r -rreti -:has waited considerably before gaining even partial acceptance, essentially because of the compleXit of therequired circuitry. However, due to the technological progress, these codes become increasingl% practicaland their use widespread. Interleaving of message bi's over a period longer than the espected fading c, leis an effective way to distribute the bit errors, so that coding techniques can be used to corret theni.a idto achieve reduction in error rates of several orders of magnitude. This is ,of course, at the expense ofthe information rate. The manner in which coding is used depends upon the nature of the signallng teshSnques employed by the link. A method that involves the transmissin if short packets of infornattn . :stwell suited to the use of interleaving, since the packets will be in general much sho:er than a fade-ur.Also, if a high percentage of packets is error-free, it is advantageous to use only error detect I witheach packet, and to rely on repeats for error correction.

In algebraic encoding, is addition to the inforntion to he transmitted, redundant informat- in i n-serted into the channel. as we have seen previously iu this Lecture. These check bits may be used for f,,rwarderror correction or for error detection only. Its purpose, in HF ssmunications, is usually t., reduce thesusceptibility to the deleterious effects of deep fadiogs. Because these fades can have durations beyond 0.1seconds, the code must be very long and rmust have a structure suitable for the correction of error bursts.The most common techniques are to use either very long recurrent codes or short codes with a condiderablenumber of interleaved blocks. The latter approach is used to randomize the effect of burst errors. Decodingof recurrent codes as well as interleaving and de-interleaving cause transmission time delays of about I to2 seconds. Code rates between 1/2 and 4/5 are used if what is required is only error detection. Short blockcodes ( 50 bits) may be used under certain conditions. Their effectiveness is however limited because ofthe high probability that may characterize the number of errors in a code word.

Present state-of-the-art transmission systems use ARQ procedures to increase cosmmunication reliability;error detection is based on the recognition of errors in the transmission of a single character. The application of systematic block codes would be already a substantial improvement. Concerning a code's ability tocorrect both burst errors and random errors, no analytical method for constructing such a code has beendeveloped thus far. However, there are useful results, applicable to specific cases : a) a subclass of cycliccodes has been found that correct both types of errors effectively - however, they either have to be usedfor low data rates, or be very long; b) random-error correcting codes can be designed that have some simul-taneous burst-correction capability, provided that the codes are not used to their fullest random-errorcorrecting capability; c) multiplying a generator polynomial of a cyclic code with d-2t + 1 produces acode which is capable of sisaltaneously correcting all bursts of length t+l, a result of practical impor-tance only for the cases in which t has small values.

An interesting application of coding to HF comsursnications is the 2.4 Kilobits/sec l.near PredictionEncoding (LPC) used in the HF links of the NATO network. In this code, the system preamble uses a Bose-Chaudhuri-Hocquenghen (BCH) error correction code of length 252 bits ( 252,128), while each digital voice'sword is encoded in a (24,12) block code.

7-12

G. CONCLUSIONS

The use of coding in HF comnunications is expected to gradually expand from present-day limited appli-cation, hand-in-hand with the progress in microprocessor technology, and with the ever greater easiness bywhich complex circuitry in mechanized.

It is hoped that this introductory lecture did strike a balance in pointing out both the potentialusefulness of codes in HF communications, and the complexity of the required circuitry. The material ofthis lecture, complemented with readings from the bibliographic references given in Section H, should besufficient introduction to coding, and enough preparation for understanding other lectures of this Serieson coding apparatus, and for approaching with confidence coding problems of the HF communications practice.

H. BIBLIOGRAPHIC REFERENCES

L1 I olomb , S.W. et al, Digital Coosunications, Prentice-Hall, Englewood Cliffs. N.J., 1964.

[21 ViterbiA.J. and J.K. Omura, Principles of Digital Communications and Coding. Mc~raw-Hill BookCo., New York, N.Y., 1979.

3] Lin,S. An Introduction to Error Correcting Codes, Prentice-Hall, Englewood Cliffs, N.J., 1970.

[4] Shanmugan,K.S., Digital and Analog Communications Systems, John Wiley & Sons, New York. NY.,1979.

15 Lucky,R.W., et al., Principles of Data Cosmmnuications, McGraw-Hill Book Co., New York, N.Y., 1968.

16 Wozencraft,J.M. and I.M. Jacobs, Principles of Communications Engineering, John Wiley & Sons.New York, N.Y., 1965.

[71 GallagherR.G., Information Theory and Reliable Coumnnications. John Wiley & Sons. New York, N.Y.,1968.

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s-i

MODERN HF COMMUNICATIONS. MODULATION AND CODING

by

P.Monsen. SoDSIGNATRON. Inc.12 Hartwell Avenue

Lexington. Mass. 02173

SUMMARY

Digital communications over High Frequency radio channels are limited by theeffects of time varying multipath signals and an impulsive noise characteristic. Mod-ulation techniques which utilize adaptive receiver structures in conjunction withadvanced error correction coding concepts can provide quality communication at both lowdata rates around 100 bps and high data rates around 2400 bps. In this tutorial paper,the multipath channel is examined and two basic constraints are introduced. When thelearning constraint is satisfied, it is possible to estimate the channel multipath gainand phase components. The diversity constraint establishes the necessary condition forimplicit diversity. For low data rate applications where Intersymbol Interference(ISI) is negligible, adaptive receivers are discussed when both learning and diversityconstraints are satisfied. An incoherent adaptive receiver is discussed for applica-tions where the learning constraint is not satisfied. For high data rate applications,both constraints are satisfied in an HF application but ISI effects are severe. Adap-tive techniques including equalizers and maximum likelihood sequence estimators arediscussed. Experimental results from HF channel simulator tests are presented incomparison of nonadaptive and adaptive high speed modems. We discuss the use of errorcorrection coding to protect against impulsive noise and show that multipath fading re-duces the theoretical performance capability by only 1 to dB when proper coding andinterleaving are employed. Performance of practical coding schemes using channel stateinformation are used to show the potential performance on an HF channel.

I. INTRODUCTION

HF radio uses frequencies in the range from 2 to 30 MHz. At these frequencies,communications beyond line-of-sight is due to refractive bending of the radio wave inthe ionosphere from ionized layers at different elevations. In most cases more thanone ionospheric "layer" causes the return of a refracted radio wave to the receivingantenna. The impulse response of such a channel exhibits a discrete multipath struc-ture. The time between the first arrival and the last arrival is the multipath maximumdelay difference. Changes in ion density in individual layers due to solar heatingcause fluctuations in each multipath return. This time varying multipath characteris-tic produces alternately destructive and constructive interference. In addition tothese channel variations, the received signal includes additive noise which may he im-pulsive in nature and it may also include interference from other users.

To provide successful communications under these sets of conditions requiressophisticated receivers and the use of error correction codino techniques. This paperdiscusses adaptive receiver structures for the HF channel and summarizes some of themore important error correction coding considerations. In Section 2 the importantcharacteristics of the fading multipath channel are defined including two constraintswhich are critical for receiver adaptivitv and for extraction of diversity from themultipath structure. In Section 3 adaptive receivers are discussed for both the neg-ligible and significant intersymbol interference conditions. Roth coherent and incn-herent receivers are also treated. In Section 4 some recent results from experiment:on high speed HF modems are summarized. Frror correction coding considerations arepresented in Section 5.

2. FADING MULTIPATH CHANNELS

For digital communication over HF radio links, an attempt is made to maintaintransmission linearity, i.e., the receiver output is a linear superposition of thetransmitter input plus channel noise. This is accomplished by operation of the poweramplifier in a linear region or with saturating power amplifiers using constant en-velope modulation techniques. For linear systems, multipath fading can be character-ized by a transfer function of the channel H(f,t). This function is the two dimension-al random process in frequency f and time t that is observed as carrier modulation atthe output of the channel when sine wave excitation ac the carrier frequency is appliedto the channel input. For any continuous random process, we can determine the minimumseparation required to guarantee decorrelation with respect to each argument.

For the time varying transfer function H(f,t) let td and d be the decorrelationseparations in the time and frequency variables, respectively. If td is a measure ofthe time decorrelation (coherence time) in seconds, then

lz

d

is a measure of the fading rate or ,ndwidth of the random channel. The quantity ot isoften referred to as the ppier Eraad because it is a measure of the width of the re-ceived spectrum when a singl ine wave is transmitted through the channel. The dualrelationship for tLe frequency decorrelation fd (coherence bandwidth) in Hz suggeststhat a delay variable

seconds

defines the extent of the multipath delay. The quantity 0, is often referred to as theiultipath delay spread as it is a measure of the width of' the received process in thetime domain when a single impulse function is transmitted through the channel.

The range of values for these spread factors for HF communication are

"t 0 .I - 1.0 Hz

"f - 0.5 - 5 milliseconds

where the symbol - denotes "on the order of".

The spreads can he defined precisely as moments of spectra in a channel model rinwhich assumes Wide Sense Stationarity (WVSS) in the time variable and Pncorrelated Scat-terinq (us) in a multipath delay variable. This WfOSUS model and the assumption ofGaussian statistics for H(f,t) provide a statistical description in terms of a si-gletwo-dimensional correlation function of the random process H(f,t).

This characterization has been quite useful and accurate for a variety of radiolink applications. However the stationarity and caussian assumptions are not necessaryfor the utilization of adaptive signal processing techniques on these channels. Whatis necessary is first that sufficient time exist to "learn" the channel characteristicsbefore they change and second, that decorrelated prtions of the frequency hand heexcited such that a diversity effect can he realized. These conditions are reflectedin the following two relationships in terms of the previously defined channel factors,the data rate R, and the bandwidth R:

R(b/s) >> at(Hz) Tearning Constraint

R(H1 z) > fd(HZ) Diversity Constraint.

where the symbol ? denotes "on the order of or greater than".

The learning constraint insures that sufficient signal-to-noise ratio (SNO)exists for reliable communication at rate R over the channel. Clearly if R - at , thechannel would change before significant energy for measurement purposes c d e col-lected. When R >> a t , the received data symbols can be viewed as the result of achannel sounding signal and appropriate processing can generate estimates of the chan-nel character during that particular stationary epoch. The signal nrocessing tech-niques in an adaptive receiver do not necessarily need to measure the channel directlyin the optimization of the receiver hut the requirements on learning are apnroxi:natellthe same. If only information symbols are used in the sounding signal, the learningmode is referred to as necision-nirected. 1hen rdigital vmbnols known to hoth thetransmitter and receiver are employed, the learning mode is called Reference-oireted.An important advantage of digital systems is that in many adaptive communications ap-plications, adaptation of the receiver with no wasted newer for snunding signals can beaccomplished using the decision-directed mode. This is nossible in digital systems3because of the finite number of parameters or levels in the transmitted source symbolsand the high likelihood that receiver decisions are correct.

Diversity in fading applications is used t) orovide redundant communicationschannels so that when some of the channels fad. , communication will still he possibleover the others that are not in a fade. Some of the forms for diversity employed in 1IFsystems are space using multiple antennas, nolarization, frequency, and time. Thesediversity techniques are sometimes called explicit Aivesity because of their external-ly visible nature. An alternate form of diversity is termed implicit diversity becausethe channel itself provides redundancy. In order to capitalize on this implicit diver-sity for added protection, proper receiver techniques have to be employed to correctlyassess and combine the redundant information. The potential for imoiicit frequencyi it arises because different narts of the frequency hand fe inp t

'hi hile one section of the band may he in a deeo fade the remainder can he used forreliable communications. However, if the transmitted bandwidth A is small compared tothe frequency decorrelation interval fd, the entire hand will fade and no implicitdiversity can result. Thus, the seconconstraint I > fd must he met if an implicitvdiversity gain is to be realized. In diversity systems a little decorrelation betweeslalternate signal paths can provide significant diversity gain. Thus it is rot neces-mary for R >> fd in order to realize implicit frequency diversity gain although theimplicit diversity gain clearly increases with the ratio R/fd" lote that the conditionR << B f does not preclude the use of implicit diversity because a handwilth expan-sion techni ue can be used in the modulation process to spread the transmitted informa-tion over the available bandwidth R. We shall distinguish between these low data rateand high data rate conditions because the appropriate receiver structures take in some-what different forms.

The implicit liversity effect descrihed here results from Aecorrelation in thefrequency domain in a slow fading (R -> at) apnlication. This implicit frequencydiversity can in some circumstances be supplemented by an imnlicit time diversity ef-

foct which results from decorrelationm in the time domain. In fast fadin; applica-tions (R > ) redundant symbols in a coding scheme can he used to provid- time diver-sity provi de the code word spans more than One fade epoch. In the slow fading arrli-cation typical of HF communication this condition of snanninq the fade epoch can berealized] by interleaving the code words to orovile larqe time oaps between successivesymr)ls in a particular code word. The interleaving process requires the introductionof signal delay lonqer than the time decorrelation separation td. In many nracticalapplications which require transmission of dilitized speech, the required time delay isunsatisfactorily long for two-way speech communication. For these reasons there ismore emphasis on implicit frequency diversity techniques in practical systems. Thrreceiver structures to be discussed next are opplicable to situations where the im-plicit frequency diversity applies. In a subsequent section we discuss error correc-tion coding techniques which combined with interleavina exploit the implicit timediversity of the channel.

3. ADAPTIVE RECEIVER STRUCTURES

We consider a general modulation system which accepts binary input data at a rate

R and converts each group of toq2" hits into a sample value which can take on one of

M values. This '-ary discrete sample (ak1

is to be communicated over the channel usinga modulation technique which forms a one-to-one correspondence between the sample akand the waveform structure of a transmitted pulse. Independent modulation of quadra-ture carrier siqnals (i.e., sin 2fnt and cos 2rf0t, f0 = carrier frequency) is in-cluded in this class. An important example with optimum detection properties is Ouad-rature Phase Shift Keying (OPSK) which transmits the sample set fak = i ±j by chanq-ing the sign of quadrature carrier nul4es in accordance with the sign of the real andimaginary parts of the source sequence {ak).

3.1 Receivers for Channels with Negligible Intersymbol InterferenceIf each sample ak can be one of M possible waveforms 0'=4 for OPSK), the trans-

mitted data rate is

R = (loq 2 (M))/T

where I/T is the transmitted symbol rate.

Many HF channel applications are signal-to-noise ratio limited rather than band-width limited. In order to maximize signal detectability, only a few waveform choicesare usually employed in these applications. When the symbol period T is much qreaterthan the total width of the muLtipath dispersion of the channel, only a small portionot adjacent symbols interfere with the detection of a particular symbol. For the slowfadinq application, the diversity constraint requires that the signal bandwidth B be onthe order of or larger than the frequency decorrelation interval f . Conditions fornegligible intersymbol interference (ISI) and adaptive processing to obtain implicitdiversity are then

f T >> 2a =L

B > f "

When the number of waveform choices P1 is small, these conditions imply a low data ratesystem relative to the available bandwidth, i.e. , a bandwidth expansion system. Thelow data rate condition for implicit frequency diversity can be expressed in terms ofthe data rate and bandwidth as

R << 8 log2 (M)

In the absence of intersymbol interference, it is well known (21 that the optimumdetection scheme contains a noise filter and a filter matched to the received pulseshape. The optimum noise filter has a transfer function equal to the reciprocal of thenoise power spectrum K(f). When the additive noise at the receiver input is white,i.e., its spectrum is flat over the frequency band of interest, the noise filter can beomitted in the optimum receiver. The optimum receiver for a fixed channel transferfunction H(f) then contains a cascade filter with component transfer functions

R(f) = 1 1

Noise MatchedFilter Filter

where the * denotes complex conjuqatlon. In practical applications, signal delay musthe introduced in order to make these filters realizable.

In general K and fl change with time and the adaptive receiver must track varia-tions. The tapped-delay-line (TOL) filter is ar sportant filter structure for suchchannel trackinq applications. The TDL filter shown in Figure I consists of a tappeddelay line with signal multiplications by the tap weight wi for each tap. For a band-

tJ

8-4

pass system of bandwidth R, the sampling theorem states that any linear filter can herepresented by parallel TDL filters operating on each quadrature carrier component witha tap spacing of I/B or less. The optimum receiver can then he realized by a cascadeof two such parallel TDL ()uadrature filters: one with tap weights adjustedi to form thenoise filter, the second with tap weights adjusted to form the matched filter. Sincethe cascade of two bandlimited lir-ear filters is another handlimited filter , in soneapplications it is more convenient to employ one TDI to realize R(f) directly. Inpractice, signals cannot be both time and frequency limited so that these TDL filterscan only approximate the ideal solution. One advantage of the TDL filter is the con-venience in adjusting the tap weight voltage as a means of tracking the channel andnoise spectrum variations.

The optimum receiver requires knowledge of the noise power spectrum K(f) and thechannel transfer function H(f). When K(f) is not flat over the hand of interest, theinput noise process contains correlation which is to he removed by the noise filter.Techniques to reduce correlated noise effects include (1) prediction of future noisevalues and cancellation of the correlated component, (2) mean square error filteringtechniques using an appropriate error criterion, and (3) noise excision techniqueswhere a Fast Fourier Transform is used to identify and excise noise peaks in t!.e fre-quency domain. The prohlem of noise filtering is usually important in handwidth expan-sion systems hecause of interference from other users as well as hostile jammingthreats.

The realization of the matched filter depends on the amount of time coherence.When the learning constraint R >1 at is satisfied, there is enough time to learn thechannel and th.- mitched f lter structure and subsequent detection process can he ac-complished cohorently, i.e., with known amplitude and phase for each multipath return.As R decreases relative to ot, a degradation due to noisy estimates increases. Whenthe learning constraint is not satisfied, incoherent detection must he used to avoidthis noisy estimate problem. Ile consider these two conditions separatelv.

3.1.1 Coherent Reception, Tearning Constraint Satisfied

When there is enough time coherence to learn the channel characteristics, an im-portant realization of the matched filter, a RAKE TDL filter, uninl the concepts de-veloped by Price and Green [31, can he used to adaptively derive an approximation toI*(f). A RAKE filter is so named because it acts to "rake" all the multipath contri-butions together. This can he acromplished using the TDL filter shown in Figure 2,where the TDL weights are derived from a correlation of the tap voltages with a commontest se quence, i.e., S(t). This correlation results in estimates of the equivalent TDLchannel tap values. Complex notation is used here in Figure 2 to represent the quad-rature components for a handpass process. The tap valles are complex in this represen-tation. By proper time alignment of the test seque*nce the RAKE filter tap weightsbecome estimates of the channel tap values but in inverse time order as required in amatched filter design. For adaptation of the RAKE filter, the test sequence may heeither a known sequence multiplexed in with the modulated information or it may he re-ceiver decisions used in a decision-directed adaptation.

An alternate structure for realizing the matched filter is a re-circulatino delayline which forms an average of the received pulses. This structure was prooosed as ameans of reducing complexity in a RAKE filter design 141 for a frequency-shift-keyingsystem. For a Pulse Amplitude Modulation system the structure would take the fornshown in Figure 3. An inverse modulation operation between the input signal and alocal replica of the signal modulation is used to strip the signal modulation from thearriving signal. The re-circulating delay Line can then form an average of the re-ceived pulse which is used in a correlator to produce the matched filter output. Thiscorrelation filter is considerably simpler than the RAKE TDL filter shown in Figure 2.

In both the RAKE TDL and correlation filter, an averaging process is used to gen-erate estimates of the received signal pulse. Recause this signal pulse is imbedded inreceiver noise it is necessary that the measurement process realize sufficient signal-to-noise ratio. This fundamental requirement is the basis for the learning constraint

R(b/s) >> at (Hz}

introduced earlier. If the signal rate R from which adaptation is being accomplishedis not much greater than the channel rate of change at then the channel will changebefore the averaging process can build up sufficient signal-to-noise ratio for an ac-curate measurement. This requirement limits the application of adaptive receiver tech-niques with implicit frequency diversity gain to slow fadinq applications relative tothe data rate. In many HF channel applications the fade rates are on the order of Hzand data requirements are hundreds of times larger.

3.1.2 Incoherent Reception, Learning Constraint tbt Satisfied

For data rate applications on the order of tens of hits/ second, the data rate Rmay not be large enough relative to the ppler spread a to accurately estimate thechannel gain and phase values for coherent detection. Tfhis condition is even morelikely in aircraft communication or auroral HF transmissions both of which have in-creased noppler spread values. When the phase information cannot he estimated, thecommunicator generally selects an orthogonal set of waveforms rather than the coherentchoices of antipodal or quadrature antipodal. Although binary orthogonal signaling hasa 3 d19 poorer distance between transmitted signals than binary antipodal, this distance

loss relative to binary antiodal signaling is imProved y uqin, more rthoo-il . a'e-f)rms. For 11-ary orthogonal signaling in a nonfadinq channel apnlication, tt'e bIerror probabilitv can be made to exponentiallv tend to zero when 7,o n ", 2(In ,r 5 .The ontinu, receiver however requires a matched filter for each ortqooonal wavefrr s-there is a significant complexity disadvantage is 'A increames.

On a fadino channel, more waveform choices implies a form of diversity. 7kwverin this application there is a nerformance limit to P hecause inlike tho coherent -e-tection case, performance Ioe, not monotonically improve with increased diversity. Ina noncoherent system, a square law combiner structure is used to sum the efl-tivediversity signals. Qualitatively when the hit energy per diversity is not somewhatlarger than the additive noise, a signal suppression effect results. Por a f Iedsymbol energy, more diversity implies a smaller value of bit energy oar diversity.Quantitatively, nierce 161 has shown that the optimum diversity in an incoherent svstemis approximately

P

oPt 310

In an NF channel application, the effective diversity order is a function of thechannel statistics. In the limit of large signal-to-noise ratios incoherent systemsare poorer than coherent systems by about 5.3 dB 161 when the incoherent systemoperates at the optimum diversity, but for other channel conditions the difference willhe larger. For this reason, it is always desirable from a performance viewpoint to usecoherent systems when the learning constraint is satisfied.

The optimum incoherent receiver in an M-ary orthogonal signaling scheme requiresa noise filter followed by a matched filter for each of the P1-waveform possibilities.The outputs of the M matched filters can he used to form a hard decision or as a set ofsoft decision inputs to the decoder. Again a tapped delay line filter is used in thematched filter to isolate the various multipath returns. Figure 4 illustrates a -DLmatched filter for one ot the M-waveforms. At each tap of the TruL, correlation is per-formed with the particular waveform for this matched filter. The correlation operationintegrates over the waveform symbol period. The magnitude squared of the correlatoroutput at each multipath delay forms the set of sufficient statistics for this par-ticular waveform hypothesis. These statistics are weighted by attenuator values whichare a function of the multipath power vs. delay profile. This profile can be estimatedby averaging the correlator output for a particular tap from all matched filters over aperiod of time for which the multipath profile remains fixed.

3.1.3 Summary of Small-ISI Adaptive ReceiverThe receiver for this small-ISI example has in general a noise filter to accen-

tuate frequencies where noise power is weakest, and a matched filter structure whichcoherently recombines the received signal elements to provide the implicit diversitygain. The implicit diversity can be viewed as a frequency diversity because of thedecorrelation of received frequencies. The matched filter in this view is a frequencydiversity combiner which combines each frequency coherently or incoherently.

An important application of this low data rate system is found in jammingenvironments where excess bandwidth is used to decrease jamming vulnerability. In morebenign environments, however, many communication requirements do not allow for a largebandwidth relative to the data rate and if implicit diversity is to be realized inthese applications, the effects of intersymbol interference must he considered.

3.2 HIGH DATA RATE RECEIVERS

When the transmitting symbol rate is on the order of the frequency decorrelationinterval of the channel, the frequencies in the transmitted pulse will undergo dif-ferent gain and phase variations resulting in reception of a distorted pulse.

Although there may have been no intersymbol interference (I511 at the transmitt-er, the pulse distortion from the channel medium will cause interference betweenadjacent samples of the received signal. In the time domain, ISl can be viewed as asmearing of the transmitted pulse by the multipath thus causing overlap between succes-sive pulses. The condition for ISI can be expressed in the frequency domain as

T-1(Hz) > fd(Hz)

or in terms of the multipath spread

T(sec) < 2wof (sec)

Since thebandwidth of a digital modulated signal is at least on the order of thesymbol rate T -Hz, there is no need for bandwidth expansion under ISI conditions inorder to provide signal occupancy of decorrelated portions of the frequency band forimplicit diversity. However it is not obvious whether the presence of the intersymbolinterference can wipe out the available implicit diversity gain. Within the lastdecade it has been established that adaptive receivers can be used which cope with theintersymbol interference and in most practical cases wind up with a net implicit diver-sity gain. These receiver structures fall into three general classes: correlationfilters with time gating, equalizers, and maximum likelihood detectors.

3.2.1 Correlation Filters

These filters approximate the matched filter portion of the optimum n IqI re-ceiver. The correlation filter shown in Figure 3 would fail to operate correctly whenthere is intersymbol interference between received pulses because the averaging nricesqwould add overlapped pulses incoherently. lhen the multipath spreid is less than thesymbol interval, this condition can he alleviated by transmitting a time qated pulsewhose "off" time is approximately equal to the width of the channel miltinath. "homultipath causes the gated transmitted pulse to he smeared out over the entire symblduration but with little or no intersymbol interference. The correlation filter canthen he used to match the received pulse and provide implicit diversity [71. In a con-figuration with both explicit and implicit diversity, moderate intersymbol interferencecan he tolerated because the diversity conhinina adds signal components coherently and!SI components incoherently. Because the off-time of the pulse can not exceed 100",this approach is clearly data rate limited for fixed multinath cnnditions. Recause ofthis data rate limitation, this type of IS receiver has had little application in IF7systems.

3.2.2 Adaptive Equalizers

Adaptive equalizers are linear filter systems with electronically a lustablepara- .ters which are controlled in an attempt toi compensate for intersymbol interfer-e oce. Tapped Delay Line filters are a common choice for the equalizer structure as thetap weights provide a convenient adjustable parameter set. Adaptive equalizers havebeen widely employed in telephone channel applications 11 to reduce II effects du- tochannel filtering. In a fading multipath channel application, th-, equalizer can pro-vide three functions simultaneously: noise filtering, matched filtering for explicitand implicit diversity, and removal of ISI. These functions are accomplished by adapt-inq a Tapped Delay Line Equalizer (TDFL) to force some error measure to a minimum. Byselecting the error measure such that it contains correlated noise effects, improperdiversity combining and filtering effects, and IS5, the TDL,. will minimize the combinedeffects.

A Linear Equalizer (LE) is defined as an equalizer which linearly filters each ofthe N explicit diversity inputs. An improvement to the T.E is realized when an addi-tional filtering is performed upon the detected data decisions. Recause it esdecisions in a feedback scheme, this equalizer is known as a Decision-Feedback Equal-izer (DPE). The optimality of the DEE under a mean square error criterion an) a moansof adapting the DFE in a fading channel application have been derived in 191.

The operation of a matched filter receiver, a linear Equalizer, ani a necisionFeedback Equalizer can be compared from examination of the received poise train exampleof Figure 5. The binary modulated pulses have been smeared by the channel medium pro-ducinq pulse distortion and interference from adjacent pulses. Conventional detectionwithout multipath protection would integrate the process over a symbol period anddecide a +1 was transmitted if the integrated voltage is positive and -l if the voltageis negative. The pulse distortion reduces the margin against noise in that integrationprocess. A matched filter correlates the received waveform with the received pulsereplica thus increasing the noise margin. The intersymbol interference will arise frmboth future and past pulses when matched filtering to the channel is employed. The 1.1can he compensated for a linear equalizer by using properly weighted time shifted ver-sions of the received signal to cancel future and past interferers. The decision-feedback equalizer uses time shifted versions of the received signal only to reduce thefuture ISI. The past 1,1 is cancelled by filtering past detected symbols to producethe correct ISI voltage from these interferers.

A general Decision-Feedback Equalizer receiver is shown in Figure 6. The firsttwo filters, the noise and matched filters, are the small II receiver discussed in theprevious subsection. The noise filter reduces correlated noise effects ani the matchedfilter coherently combines the multipath returns. The forward filter minimizes theeffect of ISI due to future pulses, i.e., pulses which at that instant have not beenused to form receiver decisions. After detection, receiver decisions are filtered hv aBackward Filter to eliminate intersymbol interference from previous i.e., nast, pulses.Because the Backward Filter compensates for this "past" Is, the Forward Filter needonly compensate for "future" ISI.

When error propagation due to detector errors is ignored, the DFE has the same orsmaller mean-square-error than the L.E for all channels 191. The err)r oropagationmechanism has been examined by a Markov chain analysis 1101 and shown to he negligiblein practical fading channel applications.

A significant problem in the use )f adaptive equalizers in the MF channel appli-cation is the requirement for rapid tracking of the adaptive equalizer weights. Simpleestimated gradient techniques sometimes called Least Mean Squares algorithms are notfast enough because of the correlation between signals on the equalizer taps. Becauseof this correlation when the algorithm attempts to adjust one tap, noise fluctuationsresult in other taps. This problem can be eliminated through the us, of Kalman fil-tering techniques fill or Lattice filter structures 1121.

3.2.3 Maximum Likelihood Detectors

Since the nFE minimizes an analog detector voltage, it is unlikely that it isoptimum for all channels with respect to bit error probability. By considering inter-symbol interference as a convolutional code defined on the real line (or complex linefor bandpass channels), maximum likelihood sequence estimation algorithms have beenderived [11,14). These algorithms provide a decoding procedure for receiver decisions

which minimize the probability of sequence error. A Maximum Likelihood Sequence Fsti-mator (MLSE) receiver still in general requires a noise filter and matched filteralthough these functions can be imbedded in the estimator structure. Figure I illus-trates the filtering and sampling functions which precede the MiSE. The estimationtechniques used to derive the noise and matched filter narameters also provide an es-timate of the discrete sample response used by the MLSE decoder to resolve the inter-symbol interference. An implementation of an MLSE receiver has been described byCrozier, et. al (151.

The MILSE algorithm works by assigning a state for each intersymbol interferencecombination. Because of the one-to-one correspondence between the states and the IS,the maximum likelihood source sequence can he found by determing the trajectorv ofstates.

If some intermediate state is known to be on the optimum oath, then the naximumlikelihood path originating from that state and ending in the final state will be iden-tical to the optimal oath. If at time n, each of the states has associated with it amaximum likelihood path ending in that state, it follows that sufficiently far in thepast the path history will not depend on the specific final state to which it belongs.The common path history is the maximum likelihood state trajectory [131.

Since the number of ISI combinations and thus the number of states is an exronen-tial function of the multipath spread, the MLSE algorithm has complexity which growsexponentially with multipath spread. The equalizer structure exhibits a linear growthwith multipath spread. In return for this additional complexity, the MLSF receiverresults in smaller (sometimes zero) intersymbol interference penalty for channels withisolated and deep frequency selective fades.

5. FI{i DATA RATE HF 'IODE'I PERFORMANCE

A series of tests on parallel tone modems by Watterson 1161, and on two serialtone modems provide a basis for modem performance comparison for a high data rate 'IFchannel -application.

The parallel tone modems divide the data into low rate parallel sub-channels sothat nonadaptive techniques can be used and II effects can be avoided. The serialtone approaches use PSK transmissions and some form of decision feedback equalizationin an adaptive receiver structure.

S.I TEST CASES FOR COMPARISON

There is considerable performance data available for the flat fading (singlepath) and the dual fadinq path suqgested by Watterson J16). This latter channel hastwo "skywave" returns which are spaced by 1 millisecond and they each fade with a 2aDoppler spread of 1.0 Hz. In general the more echoes, the easier it is for theequalizer to track because it is less likely that all echoes wll simultaneously becomesmaIl. The Watterson two path channel has thus become a good standardized test case.Watterson tested conventional parallel tone modems on this channel and the results aregiven in his report (16). This channel was also used in an evaluation of a Harris Cor-poration modem under TISAF Contract No. F30602-81-C-009g and a SIINA-RON modem underUSAF Contract ?o. F10602-80-C-0296. The results from the final reports 'rom these con-tracts provide a comparison of present day serial tone modem technology with t.e paral-lel tone modem approaches tested by Watterson.

All of the modems in this comparison are incoded except for the parallel toneMX-110 modem which used a rate 16/25 block code. Although the simulators used on someof the tests were not exactly the same, no appreciable nerformance difference is anti-cipated from this factor. The fairest comparison is on a neak power basis because 11Fradios are peak power limited. For this reason we use peak hit energy , b rather thanaverage bit energy Eb. The peak-to-average ratios assumed for the mosde m comparisonwere

SIINATRON (SIG) Modem: I dT

SFRIAL, TONEar is (MRS) 'odem: I d

USC- 10: 7 dBACO-6: 7 dei PARATLEI, TONF.

MX-[90 7 dR

5.2 MODEM COMPARISONS

The flat fading channel reqults are shown in Figure A. In the flat fading tests,the two serial modems compared perform almost the same and both gain a large number ofdA over the parallel tone modems. Mlost of this improvement is due to the peak-to-average ratio. The frequency selective fading results are shown in Figure 9. In thesetests the Harris and SIGNATRON modem realize almost exactly the same implicit diversitywhen the fading is slow. The performance advantage of these modems over the paralleltone modems is very large under these conditions.

In comparison with parallel tone modems onder the faster fading conditions, boththe SIGNATRON andi Harris modem still have a significant nerformance gain even over thecoded MX-190 system. Both the Harris and SIGATPOiM modems have not included error cor-rection coding.

These results indicate the large performance advantage that can be realized when

adaptive receiver structures are used to exploit the multipath structure of the HFchannel. This fact has been well known for some time for low data rate applicationswhere ISI is not too severe but these recent results establish that it holds in highdata rate applications as well.

6. ERROR CORRECTION CODING

Digital transmission over fading channels is impaired by additive channel noiseand a fluctuating received signal level which results in poor signal-to-noise ratiosomne fraction of the time. When the fading is slow with respect to the data transmis-sion rate, it is usually possible to determine the channel parameters, i.e., instan-taneous received signal oower and additive nnise power. Under these known channel con-ditions, one can do almost as well as a non fading channel by using interleaving tospan the fade intervals. On 'F radio channels the additive noise can he impulsive innature. Since the impulsive noise durations are much shorter than fade intervals,burst error correction coding or relatively short interleaver techniques provide pro-tection against the noise effects. In this review, we will concentrate on the improve-sent realized against multipath fadino effects.

6.1 INFINITE INTERLEAVING RESULT, A REVIEN

In a slow fading channel application typical of HF radio comnunication where itis possible to track the channel state information, the loss in detection efficiencydue to the fading is inly a few d13 provided that the channel is memoryless. Fricson1171 established this result in a comparlson of exponent bounds and capacities for thefading and nonfading white Gaussian noise channel. Of course if the fading is slowenough to allow tracking of the channel state information, it will not be true injeneral that the channel is memoryless, i.e., received symbols will not be independent.If delay in message detection can be tolerated, interleaving of the transmitted symbolsand de-interleaving of the received samples and the channel state information can pro-vide a memoryless channel condition with known channel parameters. To show that thedetection efficiency under this condition has only a small degradation due to thefading, consider the exponent bound parameter (181 for the discrete memoryless channelwhich has binary input u and real number output y.

0 log 2 q(u) 2

x y

When the rate r in bits per channel usage is less than R0 , the bit error prob-ability is upper bounded by an exponentially decreasing function of the block lengthfor a block code or the constraint length for a convolutional code. For binary sourcesand Gaussian noise channels, R0 is maximized when the source distribution q(u) isequally likely and the exponent bound narameter becomes

R0 = I - logy(l + 1) (2)

where Z takes one of two forms depending on whether the channel is fading or not. Fornonfading conditions, the y integration in (I) is only over the Gaussian noise densityand one obtains the well known result for received energy ner information bit Fb andnoise spectral density No watts/Hz,

Z = -rEb/ Gaussian Noise, N)o Fading (3)

For fadinq conditions, the y integration in (I) also requires integration overthe density of fading signal strength if it is assumed that this parameter is known foreach received y sample, i.e., de-inter-eaving of the channel state information is usedat the receiver. Thus, one finds

1 = -rFbs /N(

p(s)e d Gaussian Noise, General Fading (4)0

where s is a unit mean random variable for the received power on a fading channel. Fora Rayleigh fading received envelope, the power is exponentially distributed which givesthe Rayleigh fading result

1 = (I + rEb/N0)1 Gaussian Noise, Ravleigh Fading [5)

where F, is now the average received hit energy. For a fixed rate r and a constant R0,the dB loss due to fading is shown in Figure 10 to increase from about dR to 3dH asthe signal-to-noise ratio increases.

X j)

6.2 IMPORTANCE OF THE DELAY CONSTRAINT

In many com"-nication systems it is unacceptable to introduce delay which is manytimes longer than the fade epoch. In speech communications for example, delay must heless than a few tenths of a second whereas HF radio fading channels with speech appli-cations have fade intervals on the order of a second. This condition precludes the useof interleaving to produce the memoryless channel which is required to achieve thedetection efficiency of Figure 10. Without interleaving with an average probability ofbit error as the performance criterion, error correction coding does not even look at-tractive. Say we had a code which achieved capabity on the Gaussian noise channel.For this code the probability of hit error is zero when sE/')0 is greater than 0.69(-1.6 dRI and 1/2 when it is less than this value, The average bit -rror rate is

0.69 N0 /Ebf p(sids /.l 'Capacity (6)

0 h / 06 Co ode

For uncoded coherent phase shift keying (CPSK) operating under the same Rayleighfadinq conditions, one has for large Eb/o,

= i : erfcr',sE p(s)ds A -- , CUncoded (7)20 4 b PSK

We obtain the rather dismal result that for large siqnal-to-noiqe ratio thisideal capacity code is 1.4 dB worse than an uncoded CPSK system. The average prob-ability of error criterion results in a large penalty when a deep fade occurs. Forthis reason communication systems have historically used diversity, i.e. , the trivalredundant code, rather than coding when the delay constraint was present. The loss indetection efficiency due to fading under this delay constraint and this performancemeasure is then very large. Thus, it is important to evaluate the utility of averageerror rate as a performance measure.

In many applications information transfer is satisfactory if the hit error rateis less than some threshold and it is unsatisfactory if the bit error rate is anyamount larqer than this threshold. For these applications, average probability oferror is an inappropriate performance measure. The concept of outage probability,i.e., the fraction of time that the hit error rate is greater than a threshold, isbecoming widely accepted as a more meaningful performance measure for communications.Under this concept the power gain due to coding in a fadinq channel is exactly thepower gain at the threshold value on a nonfadin channel. Even though the coded systemmay be poorer than an uncoded system under de-p fade conditions, large coding gains cinfie realized at bit error rate thresholds where practical communication takes place.Thus error correction coding under appropriate performance measures can provide siqni-ficant power gain even when the delay constraint precludes interleavino to span thefade epochs.

6.3 PRACTICAL CODING RESULTS

Coding gains for practical error correction coding techniques on HF radio chan-nels must be examined relative to a delay constraint which allows or precludes inter-leaving over the fadinq epochs. These fading epochs are on the order of I second.

6. 3. 1 Delay Constraint PresentSpeech and certain digital data communication systems fall into this class.

Under this constraint, error correction coding and modest interleaving will protectagainst impulsive noise. Tlowever no significant coding gain against fadinq is realiz-able under an average probability of error criterion. Under an outage probabilitycriterion the coding (ain is exactly the coding gain realized on a nonfadino channel atthe Bit Error Rate (BER) threshold where the outape is determined. An off the shelf1/2 rate :onvolutional decoder .11g1 with constraint length 7 lives a codino pain -f4.6 dR at-i threshold BER of 10-4. This coding gain drops to 3.8 in at the BF.R thresh-old of 10 . Concatenated codes [201 which use a convolutional code for the inner codeand a Reed-Solomon code for the outer code can do significantly better. Since thisdelay constraint condition reduces to an evaluation of coding gain on the non-fadingchannel, only a limited discussion is warranted here.

6.3.2 No Delay ConstraintWe have shown that theoretical performance on the fading channel can come within

1 to 3dB of the non-fadinq channel if we interleave the channel state information aswell as the soft decision outputs from the modem. It is of interest to examine prac-tical coding schemes to determine realistic coming gains with this approach. Itaqenauer1211 has computed the performance of a rate 1/2, constraint length 7, convolutionalcode for different quantitization levels of channel state information and decisionvalues. The following nomenclature is used in the comparison.

f

Unquantized Decision = Y SOFT (Y.S)

1 bit quantized Decision Y HARD (YH)Unquantized Channel State A SOFT (AS)1 bit quantized Channel State = A HARD (AH)No Channel State Information = A NO (AN)

The result of his calculations are reproduced in Figure 11.

This code has a 4.6 dB gain at a HER of 10- 4

on the non-fading channel. It re-quires an Eb/?:0 of about 7.2 d1 under fading conditions when both decisions and channelstate are unquantized. This represents a coding gain over the non-fading channel nfabout 1.2 dB. The loss due to the fading is then only 3.4 dR. This small loss can hebetter appreciated by comparing the coded performance with dual diversity in Figure 11.It is also of interest to note that one hit quantization on the decisions anA channelstate does as well as unquantized decisions alone.

7. SUMMARY

For many HF communications applications, the channel msay be considered to heslowly fading. Ile have shown here that when this slow fading is exploited to learn thechannel, combined nodulation and coding techniques can remove msuch of the fading effecteven in high data applications where intersymbol interference is a serious prghbem.Experimental results have been presented showing successful conMunicltion using equal-izer nodems in a high data rate application. Fading performance of practical decodinitechniques has heen shown to be within a few dIB of coded systems -n non-fajino chan-nels.

REFERENCES

[11 P.A. Bello, "Characterization of randomly time-variant linear channels," IFEFTrans. on Comm. Systems, Vol. CS-ll, op. 360-393, December 1963.

121 L.A. Wainstein, V.D. Zubakov, Extraction of Signals from Nbise, Prentic.-Hall,Englewood, N.J., 1962. Chapter 3.

131 R. Price, D.E. Green, Jr., "A communication technique for multipath channels,"Proc. of the IRE, Vol. 46, Nb. 3, March 1958, pp. 555-569.

141 S.M. Sussman, "A matched filter communication system for multipath channels," IRETrans. on Information Theory, Vbl. IT-6, Nb. 3, June 1960, pp. 367-372.

151 J.M. Wozencraft, I.M. Jacobs, Principles of Communication Engineering, John Wiley& Sons, Hew York, NY, 1965, p. 291.

161 J.N. Pierce, "Theoretical limitations on frequency and time diversity for fadingbinary transmissions", IEEE Trans. Communication Systems, Vol. CS-lI, June1961, pp. 186-1.97.

171 M. Unkauf, O.A. Tagliaferri, "An adaptive matched filter modem for digital trono-scatter, "ICC Conference Record, June 1975.

131 R.W. Lucky, J. Salz, E.J. Weldon, Jr., Principles of Data Communications, McGrawHill, New York, NY, 1968, Chapter 6.

191 P. Monsen, "Feedback equalization for fading dispersive channels," IEEE Trans.Inform. Theory, VI. IT-17, pp. 56-64, Jan. 1971.

1101 P. Monsen, "Adaptive equalization of the slow fading channel," IEEE Trans. onCommunications, Vol. COM-22, No. 8, \Aq. 1974.

1111 D. rodard, "Channel equalization using a Kalman filter for fast data transmis-sion", IBM J.R. Development, May 1974, pp. 267-273.

(121 E.H. Satorius, J.D. Pack, "Applications of least squares lattice algorithms toadaptive equalization", IEEE Trans. Communication, bl. COM-29, February1981, pp. 136-142.

1131 G.D. Forney, Jr., "Maximum likelihood sequence estimation of digital sequerces inthe presence of intersymbol interference," IEEE Trans. on InformationTheory, May 1972, pp. 363-377.

1141 G. fngerboeck, "Adaptive maximum-likelihood receiver for carrier-modulated datatransmission systems," IEEE Trans. on Communications, Vol. COM-22, No. S,May 1974, pp. 624-636.

(151 S. Crozier, et al., "An adaptive maximum likelihood sequence estimation techniquefor wideband HF communications", MILCOM '82, Conference Record, %bl. 2, pp.29.3, October 1982.

1161 C.C. Watterson, C.M. Minister, HF Channel-Simulator Measurements and PerformanceAnalyses on the TSC-l0, ACO-6, and MX-190 PSK Modems, Office of Telecommuni-cations, Boulder, Colorado, Report No. OTR 75-56, July 1975.

i

171 T. Frt s,)n, "A a sianchinnel with ql~w i1,nn", tF17 Trnnq-.cti-n , In 'tlon Theory, May 1970, op 3535.

& 'ons, Iew Yo)rk, NY, 1965.

1191 inkahit -,rporatiin, LV7026 COIEC hrochire, ';.n Diegoo, -4.

1201 G.C. Fornev, Concatenated Cotes MIT Press, am!ri,1, MA, 'q66.

(211 J. Haqena~ier, "Iliterhi-decodinq of c)nv'litional ,Ies f~r fidn7 In ir "nels", Proc 1980 International 'urich Po'inar on iiitll 7 ini,- tie,G 2. 1 -G 2. 7.

FI C:RES

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FROM IlAr !-ENACEP E21]

EQUIPMENT: ANTENNA SYSTEMSby

L.E.PetriePetrie Telecommunications

22 Barran StreetNepean, Ontario K2J IG4

CANADA

ABSTRACT

Some antenna fundamentals as well as definitions of the principal termsused in antenna engineering are described. Methods are presented for determiningthe desired antenna radiation patterns for an HF communication circuit or servicearea. Sources for obtaining or computing radiation pattern infermantion are out-lined. Comparisons are presented fetween the measured and computed radiationpatterns. The effect of the properties of the ground on the antenna gain andpattern are illustrated for several types of antennas. Numerous examples aregiven of the radiation patterns for typical antennas used on short, intermediateand long distance circuits for both mobile and fixed service ope-ations. The app-lication of adaptive anter: a arrays and active antennas in modern HF communicationsystems are briefly reviewed.

1. INTRODUCTION

The performance of many HF communication systems is seriously deoraded ineto the use of unsuitable antennas for both transmitting and recoivinq. The an-tennas should be designed to efficiently radiate and receive energy in the desireddirections. A method is described to determine the desired elevation and azimuthalangles of radiation. Souces are presented for obtaining antenna radiation patterninformation on typically used HF antennas. The application of prediction tech-niques is described to determine the best or the most cost effective antenna fromseveral being considered for an HF service. Examples are presented of the relia-bility of communications for several types of antennas. The advantages and un-ttions of adaptive antenna arrays and active antennas in modern HF communicationsystems are briefly described.

2. RADIATION ANGLES

Until recently, the desire: elevation angles of radiation for a fixed ser-vi*e were calculated manually based on the use cf a E region reflecting height of110 kms and a constant F region height between 250 - 200 kms. Various types ofnomograms or charts were used to aid the design engineer in these calculations.At certain times and seasons, the use of a constant F region height yields signi-ficant errors in determining the elevation angle of radiation. In addition infor-

mation on the variance on the elevation angles is required in specifying the beam-width of the desired antenna lobe pattern. More accurate and additional informa-tion can be obtained using the advanced prediction methods described in a previouslecture. The elevation angle is computed for all times, seasons and periods ofsolar activity over which the HF service is being modelled. 'rho results of jhesecomputations are presented in a statistical form as shown in Fig. 1. These compu-tations are based on the selection of the mode of propagation with the leasttransmission loss. From these results antennas can be specified and types select-ed that radiate or receive efficiently at the desired elevation angles. For mobileservices and other types of services providing coverage over a large geographicalarea, computations of the elevation angles are done at representative lo'ationsand weighted by taking into account the density and location of the communication

N terminals.

3. TYPES OF ANTENNAS

An engineer designing an HF communication system requires information on theradiation pattern of various types of antennas inorder to select one that meetsthe particular needs. Several reports provide graphical information (Dept. of theArmy, 1950; Thomas and DuCharme 197" on the radiation pattern as a function ofelevation angle at the centre of the main lobe. In these reports, patterns arepresented for antennas typically used for HF communications. The antenna gain ina specified direction is given by (Barghausen et al, 1969)

S10 1 r4w Power radiated per unit solid angle]G = Og 0 Net Power accepted by the antenna

The not power accepted by the antenna includes ohmic losses, losses in the groundbelow the antenna and the radiation resistance corresponding tothe power radiatedfrom the antenna. The antenna gain does not account for impedance mismatch losses.Vertical radiation patterns are shown for

a) horizontal half-wave dipoleb) rhombics, types A, B, C, D, and Ec) half rhombicd) inverted L

!D-A13011 63MMOOERN HF COMMWIICATIONSIU) ADVISORY GROUP FORAEROSPACE RESEARCH AND DEVELOPMENT NEUIILY-SUR SEINEiFRANCE) JI AARONS ET AL. MAY 83 AGARD-LS-127

UNCLASSIFIED F0 17/2.1 NL

IINE Ii111

46,~E 2

IDI1. 25 14 1131.6

MICROCOPY RESOLU)TION TEST CHART

NAMTh9L I RCEAU OF STANDADS -I963

e) sloping V

f) horizontal log periodicg) vertical antenna

The three dimensional pattern for all the above antennas can be calculated usinga computer program developed in the U.S.A. (Barghausen et al 1969). For each an-

tenna, the physical dimensions must be specified as well as the conductivity anddielectric constant of the ground. For example, a rhombic requires specificationsfor a feed height, leg length, and semi-apex angle while a vertical antenna re-quires specifications for length of antenna, length of radials, radius of radials,and number of radials.

The type of ground generally has a limited effect on the main lobes of thepattern for horizontally polarized antenna. However for short vertically polarizedantenna, the type of ground can significantly alter the efficiency of the antennaand its power gain. The effect of ground on the antenna radiation pattern is shownin Figs. 2, and 3 where for

good earth =10-2mho/m 4

poor earth = 0 = 4

sea water o 4 = 80

A recent survey in Canada indicates the following types of antenna are be-ing used for HF point-to-point communications on short, intermediate and long dist-ance circuits.

Short Distance Intermediate Distance Long Distance1000 kms 1000 to 4000 kms 4000 kms

half wave diploe rhombic rhombicinverted L half wave dipole log periodicvertical vertical beveragelong wire inverted Ldelta

Over 80% of the ground based stations used broadband antennas such as the Delta,Rhombic, Beverage, and Log Periodic to enable operation at any frequency in theHE band without a tuning device.

4, ANTENNA SELECTION

Prediction techniques are also used to select the best or most cost effec-tive antenna fromseve-al antennas being considered for an HF service. The re-liability of communications is computed for each antenna at representative timesover which the [IF service is planned. For each antenna the average reliability forthe representative times is calculated and the best or most cost effective antennais the one with the maximum average reliability. An example of the average re-liabilities for three types of antennas are shown as follows for an iF circuitfrom Churchill to Inuvik.

Type of Antenna Average Reliability

Rhombic 83.5%Horizontal Log Periodic 78.4Sloping V 86.1

The reliabilities were computed every hour of the day for January, AprilJuly andOctober and R12=10,40,70 and 100 in order to simulate the IiF communication con-ditions expected from 1981 to 1985. The Sloping V antenna exhibits a higher rr-liability of communications than the other two antennas. In some cases the designengineer may wish information on the statistics of the variability of the reliabil-ity for various types of antennas. Such information can also be extracted fromprediction program calculations. An example of such information is shown in rig. 4.The lower values of reliability at certain periods for Antenna #I compared toAntenna #2 may be of more importance than the average reliability figures.

5. MEASURED RADIATION PATTERNS

Measurements of the radiation patterns for HF antennas are reported usingan aircraft to tow a small aerodynamically stabilized Xeledop ( Petrie, 1978;Petrie 1979 ). The Xeledop consists of a battery operated transmitter and shortdipole antenna which is towed in a stabilized position enabling the measurementof patterns for horizontally and vertically polarized antennas. The transmitterfrequency is crystal controlled and can be operated in the HF and VHF bands. Forcertain measurements, a ground based radar is used to measure and control therange between the aircraft and the antenna. With such a measureemnt facility, thesmall scale variations of the azimuthal pattern can be measured for both verticallyand horizontally polarized antennas. In addition for vertically polarized antennathe small scale variations in the elevation pattern can be measured at specificbearings such as along the boresite of an antenna. Several examples of the measured

radiation patterns are shown in Figs. 5,6,and 7. In most cases the main lobe ofthe pattern agrees with the computer calculated patterns to within 2 dB when theelectrical properties of the ground are uniform. At elevation angles less than 5degrees the calculated radiation patterns are at times in error due to variationsin the terrain in the vicinity of the antenna. However in the majority of cases,the computer programs provide a cood estimate of the main lobe of the antenna butthe magnitude and location of minor lobes are not prdictable with any degree ofaccuracy.

6. ADAPTIVE ANTENNA ARRAYS

An adaptive antenna array is designed to enhance the reception of desiredsignals in the presence of jamming and interference. Such systems have been builtand tested in a variety of communications applications including mobile, seaborneand airborne platforms (Hanson, 1977; Effinger et al., 1977; Reigler and Compton,1973; Compton, 1978; Horowitz et al., 1979). The utility of adaptive arrays forcommunications lies mainly in the ability to reject the undesired signals by vir-tue of their spatial properties. For a comprehensive basic understanding of adap-tive antennas an excellent book has been published recently ( Monzingo and Miller,1980

Many adaptive arrays operate on theprinciple of maximizing the signal-to-noise ratio or minimizing the power in the undesired signal at the output of thearray by subtracting a reference signal which matches the desired signal fromthe array output signal. Various techniques are developed to do these complexcomputations quickly and accurately (Reed et al., 1974; Horowitz, 1980; Widrow etal., 1976). Some of these techniques can be implemented using digital, analogueor a combination of analogue and digital data processina methods. In order tocharacterize the desired signal so that a reference signal can be generated, apredetermined pilot signal may be incorporated into the desired communicationsignal. The pilot signal may take many forms: an additive pilot signal, a mul-iplicative (spread spectrum) code, a time multiplexed pilot signal, and a pre-letermined set of times when the communication signal is not on. In the presenceDf a jamming signal it is desirable to code the pilot using a predetermined securezode.

The degree of interference protection afforded by an adaptive array dependson various factors but typical values of protection are about 30 dB. An array ofN elements can provide prot tion against N-I interfering slnals. Adaptive arrayswhich use the LMS algorithm (Widrow et al, 1967) are reported to adapt to multiplesources of interference in many seconds for a 3kHz signal bandwidth. Arrays pro-cessing data using the matrix inversion technigues make more efficient use of thesignal information and adapt in less than a second for a 3 kHz signal bandwidth.The time varying HF signal environment places certain limitations on the perfor-mance of adaptive arrays and requires certain array configurations in order thatadequate performance is maintained(Jenkins 1982).

7. ACTIVE ANTENNAS

An active antenna consists basically of a rod or dipole and an RF amplifyingdevice. If the noise level generated at the amplifier output terminal is less thanthe noise pickup by the antenna, an active antenna system is capable of supplyingthe same signal-to-noise ratio as a passive antenna. The atmospheric noise levelfrom a one meter length rod is generally greater than the amplifier noise when therod is coupled efficiently to an amplifier. The advantages of an active antenna are

- The short physical dimensions of the rod- The wide frequency band of operation (ie 2-30 mHz)- Fixed output impedance of 50 or 75 ohms

The main disadvantage of the active antenna is the intermodulation distortionproducts which are often generated by strong interfering signals. The use of VMOStechnology in the design of the RF amplifier will improve the dynamic range overwhich the system can operate with out intermodulation products. However, thesedistortion products can seriously degrade the performance of an active antennain an environment with high RF noise levels.

REFERENCES

Department of the Army, "Radio Propagation" TMII-499, United States GovernmentPrinting Office, Washington,1950.

Barghausen A.F., Finney J.W., Proctir L.L., and Schultz L.D. "Predicting LongTerm Operational Parameters of High Frequency Sky Wave Telecommunication Systems"ESSA Tech. Report ERL 110-ITS 78, 1969.

Compton R.T. "An Adaptive Array in a Spread-Spectrum Communications Systems",Proc. IEEE, vol. 66, 1978.

Effinger D.D., Jones W.R., Masenten W.R., Miller T.W., Tees W.G. "Final ReportUHF Adaptive Array Development Program" Report FR-78-14-263 by Hughes AircraftCo. for Naval Research Labratory, 1977.

9-4r

Hanson P.M., "Application of Adaptive Array Technology to HF Communication Systems"EUROCON 77 Proceedings, vol. 1, 1977.

Horowitz L.L., Blatt K., Brodsky W.G., and Senne K.D., "Controlling Adaptive An-tennas with the Sample Matrix Inversion Algorithm" IEEE Trans. Aerospace andElectronic Systems, vol AES-15, 1979.

Horowitz L.L., "Convergence Rate of the Extended SMI Alogorithm for NarrowbandAdaptive Arrays", IEEE Trans Aerospace and Electronic Systems, vol AES-16, 1980.

Jenkins R.W., "Implication of the Time-Varient Properties of the HF SkywaveChannel for the Design and Performance of Small Adaptive Antenna Systems",AGARD-EPP Symposium "Propagation Effects of ECM-Resistant Systems in Communicationand Navigation", Copenhagen, 1982.

Monzingo R.A., and Miller T.W., "Introduction to Adaptive Arrays", John Wiley andSons, 1980.

Petrie L.E., " Xelodop Antenna Measurements at Trenton Receiver Site", PetrieTelecommunications Report, December 1978.

Petrie L.E., " Xeledop Antenna Measurements at Brentwood Receiver Site" PetrieTelecommunications Report, March 1979.

Reed I.S., Mallet J.D., and Brennan L.E., " Rapid Convergence Rate in AdaptiveArrays", IEEE Trans. Aerospace and Electronic Systems, vol. AES-10, 1974.

Reigler R.C.,and Compton R.T., "An Adaptive Antenna Array for InterferenceRejection", Proc. IEEE, vol. 55, 1967.

Thomas J.L. and DuCharme E.D., "HF Antenna Handbook", Communications ResearchCentre Report No. 1255, 1974.

Widrow B., Mantey P.E., Griffiths L.J. and Goode B.B., "Adaptive Antenna Systems"Proc IEEE, vol. 55, 1967.

Widrow B., McCool J.M., Larimore M.G., and Johnson C.E., "Stationary and Non-stationary Learning Characteristics of the UMS Adaptive Filter". Proc IEEE,vol. 64, 1976.

ACKNOWLEDGEMENTS

I wish to thank R.W.Jenkins of the Communications Research Centre for providingassistance and material on adaptive arrays.

WINNIPEG-BAKER LAKE

o *

0

10 15 20 25

Elevation Angle (degrees)

w

HORIZONTAL HALF-WAVE DIPOLE AN}TIEN\NA9 01 ,ERECTED OVER THREE TYPES OF GROUND

10' poor - good-- sea-water ....

Bear ing - c egrees

400.

20*

10.

-15 -10 -5 t0 +5 410 #15 -20

POWER GAIN RELATIVE To !SOTEOPIC (dl)

VERTICAL ANTENNA ERECTED( OVER THREE TYPES OF GROUND90*.0 poor- good--- sea-water ..

TLength - 0.25 wave'engths

0**

POWER GAIN RELATIVE TO ISOTROPIC joll

F'ia. 4Antenna #i

C-uaI

u Antenna #2

405Q0 7 09

00

40 50 60 10 809

00

104

310,2

2\50

-300

S LOG PERIODIC

2 _______0_____ _ .- :7 FRE.QUENCY 5.1 MHZ

ELEVATION ANGLE 4.5 0 o

280,100

23120

Antennia Aadiatior. Fattern

evat~o O l2ane

70,~

25 20 -5 -0 -5 *N +5o1

300 >< so

290 ?o

280~ 4 0

270- 20 fXQVENC -.soM- ELEVATION ANGLE 9.10

260*. loo0

250', o

240' ' , 12C

HF EQUIPMENT: RECEIVERS. TRANSMITTERS.SYNTHESIZERS. AND PERIPHERALS

hsQ.C. W Iislsr

The %IITRE Corpor at (ionBedfrd. Niassachusetts

017301

SUMMARY

Although long di stance coolimnicat ions x ia sateli ites has dominrated the last t decades ot radiocclo ptnentdrewelopment, high lrequency (HF) radio equipment is experieti g it high rechnmologs renaissance

Satellite ss sterns no%% transmit qualirs loss data Tate curimunications and rlatigarirriraids to riohile usershut the loss cost and surtirabi lit% attributes of 11F tad io aric again being recogn i ed. Fincrgi ng tess s\ sienisautomate neissork operar ions %k hile adapt ing to pr opagat iom toiditloml'. Ho%%sCser, neitIher ness replacericit radi,nor new% svstins turni sh the potent rial capahi lit ot state-ut-the-a it conmpnnts. This nape r suronra ri/es theads ances in equipment. ss stemvs, and comiponents.

INTRODUCTION

Betfore the adverrt ot satellite plaitfrms, soiph istieated H F proipaga in rrand svst em rescaitel piori Ised

inirnsd capabilitN dur-ing disturbel~d infiinpheici piopagatin otditions. Hosses er. satellite relaNrscaptured treiriaginatins arnd pocketbooks, of the C01oriliiCatiOls Corttrrrorriis irr the rtrid Ios. Consequeritn extarrr 1Fs~stenis aged ss bile satellite systems %%ete irmplermented. During peacetirme. satellit es ste nis transmit quallirs losdata rate cumrnunicat ions arid may igar ion aids to robi Ic users, but there is rioss reness ed inte rest inr tie ru% crrsr arrdsurvivability attributes of HiF radio. At this rime. %%heri old If prinme nsstems need replacermenit lor Irgisicalreasons, the need for loss cost commnunireartiorts that can su site janinrg. nuic leart-t ct ts and space ssart at-e t s rrsatisfied. The HF rernaissanice is the resporrSe to this LrlleriCgC.

Loigi stical replacement prouorernrts which do pros ide ness capabi lit irs are ted ressing thec attrmiion otvacuum tube radio equ ipmrent over the last decade. Procu rinrg organ iatinons r vpica Ill compi le spec icat iiiricomprising state-of-the-art and nic%% capabi lit iss otlet-ed b% coipe irig endors. 1 rr r g rated circU its include mricroi-processnor and synithesizer elerrents which hate led to, tes circuit architectures. The I irst of thde tirlrrs irrg thresect ions describes: Receivers; Transceiversand Antenna Couplers: arid Audioi Charinel Peripherals.

Emerging nes stei uriiraere i r pri ns sbl dp tinliripatgatininLci rtrimrrrs. The seer md.section describes:

ICS-3 Simutltaneous Itrequetrc -agi le t r anrtissinr and r ecep iuon on broard ships

SEL.CAL..Sc-ann ing, arid Channtel Es aloat imriAo rrrni d es gai a ise n

Packet Radio Autonormous mnsSages firid their statrhrorugh nodes.

SNOTEL Meteor trails. sponradic E. tresit al ditffractrnri. ailtratt ci t. allit loss prrrbabilir ptrrpagar ionto serv ice 500 stations.

These ssstems are representative t %%il ht riaN be accomnplished to satists specit ic needs. The equipmrent des duped

raothsssmisas o unique. More general capabi lit ies mta% resulIt fTrm the use nt the tress In gi sik al rs-placcrrieriraisand computers. Hts esr. neither ness replacemtisr rtadiris norr ness sy stems futni sh the pot en tia ca pabi lit%

uttered by state-of-the-art components.

The third sect in - ss bh describes the t runt ier nit the state-olt-thle-art comiponrenrt s. l rico silr: Rccis eDy* namic Range and Norise Figure: Frequetic\ Synithesizers; Pirsser Amuplitiers: Widebarid Antenna S sicrns.Proicessoirs: and Real-Time Clocks.

A network control tacilit\ commonly cominprises indis idual componentis of superirrrqualmt because space isnot constrained and cost is minimized through reduced labior. Ho%%ever, compromises amonig p-rtrtrat c. sr"cand cost considerations are usually necessarv four the large numbers of mobile or trantspiortable stations.

LOGISTICAL REPLACEMENTS

Evolv ing equipment designed to meet continuing needs has \ iclded significant imnpros emnert iof receis ers.transceivers, and inputoutput devces. Simplified operations through electronic control is a domintant impetus.The use of many highly trained manual operators is held ito be economicall\ insupportable. Operators base otherduties: equipment that relieves onerous tasks such as radio tuning and radio monitoring is stelcorrie. The technicalchallenge has been to obtain electronic control without losing the pertormance available frojm the best manualequipment.

Receivers

Thev he, pi'cdc.esiii' uo'sci I Ia rIrc 'cCC Vi' usc ganged. rid ni inhand. Iricthan r a I -IL IIg r adio I I cq tc I c%IRF I tiriplIi I icrs and loca Is oki raot'I. Ncss r'cccisc Ii tic h% fociai Ine,,i Iarimi si rrhe, i/crs under' d tiia I cirriroI A.I ILdit, nrif uise irarnhand RF prcewlctr un because OCIent kiii pr:sCIi0e 1r ii iririi rdCcd si, Mucrh iii111CM1 1ii 1n0nr stao sc air Increcased rrisc Hooii t comiporsed oll high-iuider i iii rriridulatinI IM Ipi'i ioc is I ridges all cunpp resscd h%halinrg a fir', irrtcrrrrdiaic I icquL:nes Ili) Ill the %vN-' high I r'Cqtrerrc (\'it ban&id Th clnC,,tItr'C i11ilatcd iniFiguinre I has irhiai medi almost i0eisal accetrance

peirrmnrce imrinemci has3 cCViI Ill dCCI-Casirg itrin-cud nhjI\Cr 110iriirCar'irs \0101i is licirn siccit rcd b\s therir'd-iu'der irtrcepr pminir sinigle Mtni ucc bi hairiied I ruin rieasurirg the 21 - t, iri-nidulation pi'odmrc Isiliosrr-taicd iii Figuic 21. ;r-caer' rthan 30,d1rii isorirairalicb hL rrirIrIci'craecr rs iihiii 14,1 dH rine Iivu.1,'rhis irrpr'rrsnrn in liricar nirii~i icc iririoui IWs cspnrscd tinilrijiics iii tile 11rs1' 1 iltct is inch is tilrcrr arrar'r'rrsshand crs sal lartice riciiorki). SirLihs/cr phrase rriis is nrirs the durrliiraril dICct-rCrii i disc iirriiragain,[i a sirong adjaccrrr signal, as lihsir arcd in F'igurec 3. Thic I irmri signal .lcisasa hit ainisci:laim. kN iti s1\kIchIticnrphase risc in 1nrV r'cccisci' loial irseillnriri'icipi'icar-s'' h% acting as tice Signal. hicticc tile lcrii i'cipr'icaliriig.'' The irnal oiscillatoir snhesiuers iire a couriper iscl coiinical comipirmise irrinrg ihe dichototmir

heci n isci unirig specd and phasc nistbrsiiia ' pei ca nir rhutrrici iiiii e\isr rri ivi old rtche isuppi ried hi Isl stei anal sis .Th inn Ipat (iii s\I iihcsi/cr's i il be g 'caIC r'Ihar il U d%.anageut digia raticqirelicIunirni Lt. hich call he aceirnp i shcd It Ili Ouici ay Cital I cqUOrI %i iourniir. S~ inbsi/crs can pius ide al itia rilL. qminkk

I icqueirci sclenriui.

Tlc.lre'aiiialcurvc'rein. hthi. unis Ieneisc\ li irisrtardi rig. Nuink ri acalInrc oscrnriihehrlic'i'lpr'ilessul' ar a r'einiitc location. hiri checkouit is nrrucli 1tinarc Lun jul hnirirrsrcupc ir iii' ll'iMans icce cs s plrs'buiiiriarid iiiraic-rit-san tuning iii aid iranirial I r'cqcrcncs cciri.'i ciici didigital Irecquctle\ 'scict iionl enharnccd lit tile abilmr iti slc r l.ucincics pillsidcs ain Iranta icdccini Iiupci'ar imrai lahbir.

fahle I lissiipical recenir cipci'Ii'niCc pararr1CicI'. Nnic Ila hial LIL1Aiinicii CulnpI ill bIMr iiiiss I.i'cprl'sspceit catirrnmirserall tiuc dciai as a lurictiiono rqec,\ihnn dha iSB hnck

Transceivers and Antenna Couplers

NVi i r'arrSdcisers arc Iuutrin rg (Ile lead )It digirahik coirirulied l'ccci\cr'. Tiarisceieis crDIMUr iii be hdesignecd ptimnarii sil ih mo3irnduioun Ili piu dirig a1 Lowie handickidth Channel I 'rntl sit til e irtirciace liidigital data pcriirhei'ais is litciiedcu. Fast auitomrlatic aiilira Iurninig I, bcoiinrg as aribie:. ile minicsiatnns-itthCsc dIcNCIO1ipncnis iiiiiis

Remotiicomumi'iiid lirairecisci, soskc scrcal ptiliirs. .-'orci'rif ciickpit space is miimrial. as is iridit.iici h%Owc )i\ Sc s/c tititile un iii hris il tilc Iff it anisciitci cririuicrins shimn ii i Figure 4. Nmt he i, lar'ge si/c Ii tice

arrcrricn\ric sIll, n has heenciil sigrncd it)iaii'i' I kI iII C1)Irl sLIrr1 Lice ci0i'It'afil Is. Maiipac ks riced Itiie ec~mIui'niic hr) )he iipci'arur iir Irrcirru Inig Ithe padm k. Tact ical goiin sLLIxchicics ares\ Irlcahic it) atiack st)i ihai iiiing cu ii

thimuig libhel' iipii si' is \\Il is prili ided Thre ciuiiiciricirc (it cirriutci' icinninal diriir ii through a standarddicph"Iuic Irriertane is gcrnCIaJii JckIrIocin edd sirarr 11slarid is asafiahic iiarliraicur radio raislelci'.

'lie capaii to iii eunte rhe roiling coiol'ri can alsii pros ide I irjCIrns Scaning tii huippirig. SVser aiiiuiircrrckiatord iiaripaki riiis0 hasc beeI n riilliCd fiv deiuiirraiirs tii ie Imlemientatioini niha NsIelllrfirpics Ssicriciiuk I iiepi, s chic h arc gnn iai il acin rg cscept, apparciri, tot exe'scral Euroupeai'inusI icqireid's-hi ppirg" appikati ois.

Oiliers cuurriiruc Iticarripll ic. arid thc arircnra runer'. The riced liii a VHtic\tcriuur iii' iirtci'uipei'ahilitiis asresuiicdti r ranscers Li I thai esxtend ll,) uthe \I'HFr'cg ii ii ht, ci minon is' assenibi li-tHFaid'lF uipiinaeiouidruptieher' _Ncsi equipircin e\terdirig iirrotile \'IIF r'cgionl \ill I aciiitaic rue tisei dis ci-sc prolpagationi nudes sit, I asgriiirrd "a ic. unique dill 'actir irppi unrirrivs. arid rileteri'iai.Iorsfroe r imiportanita rrrlesdigdisturbecd cnutinii,s The curls ing rr'aIISCCisCv UrItVIrIa cOiipiiiig arid powLer arrplil icr con igorarions i'd cci-xistinrg spatepJnrhlemusarid the ness souin rs aflirded% hs epiacenirrer equi pmnrt.

'lianpiur a n rd rrihi nenshas adi aird licl In rile Lai decade besid ihc autinriaric itining oIiraririhaid rrirrr~rs Anenn cople' rilig seed uta I ractin ii a secondf areiubtairiahie ini unirs \010c ILLss it'll

anruIcl elaxsrnpiiare poisitirns. liric'rulrl' ircchariisriis taking senruirds tih~edetiillu illi tt ases, thle i'eiiriiii't% rrehnrciniiiiierstca'rhidh high sihiatiniirat sormea aI callt ancira iiatiiis)

Si rice hurnaln speech:I cilulluir ica (tniirs does, rno depend onl phasNe urn t uicdcia\ccrctrs c'.S ai tteiepho ne icr's ice pinc rice hats been i enjIpliasi/C sharp ariipi Ui d reSirrlise lii icrs shich pass ()il,,t~ it, 1(1011/ItI rquCIic sand trmrigik at tenroate f requcieis out side: iii ths reg io n. Phase cha ract eii'sis %kinh alit irrpi ii antlIii high 'atclt a tiratsmi is ii rs %%cetoii i imiside rei iiir lde r wice tad i ccisers. The r ran sinfleicr and lectis tc'hanniel tilters i.ause espetialil iliarge phase sh iiis near thc band edges. 'This dLiiii in I run, finicar phase isteqocnrts causes- ringing and connsequernti\ intevi, iniburi ininter'rnce ishen reeis ing sururi tlara anti leads iti

degraded hit timingun parallel trofledata.

simiilar aind sho\s coiiideriohcI. tipic A ti~itsiicl ICkIelser link %%ill hic 1511 I iw of c IIIIC - hiP[ll," Inlllid"IiispeCil ic pi(Ihitct:iiiil I'Lil is likse]\ I0 Iiaic' J LiiiiijIUC 11aii1111),ts 11hi1 Al~ lets heI..iis b-INlii.-

1 lilth 1111)\ oIdll ati l'

narruest banldpajS has I iiallI\ beer Illqie IIC ~_tIIIa!I NIIe 1 % tMCIIIlt1,11. at Italeti IcIss-liIIt C I I A iieIitia tItrt Iisa iatiCfilter at anl iniernedifiaie cqtieii \ ,sitl, It it 4;: IN) I/.

[)ata Signal Phase jitter call tIll I ol] lial o's lllatlll iiistlihilitie- Is1eCI hi 1(1\k Q) iiIts I Iit t. phaiSe

not particulalrh nits% hut lii o% cIC Ill HII e I II L t ll [Itis I lialliiiel - .\Ic LIIII csIII l..l'l b II I hI\Ib hI idi I i t M,11 Il. LIllhi. scioii t. Tianisstn lscilIla I oi circuits hai e less illciIIllini5 11111 t1~i C111\ IN 1i110iC I ki n oist' anI 0lI- telUs-s\nticsiter designs si hi.h alt.iciinuaie slme phase-lit.k looip -,iIscIlat sI ( deha IdLs. SoiltI Itll~ I .I[1,111 1 15 C]CIIc ause deg raded datIa peilruimalicC JAC hI I is Incj phase -It Iherit Ii C I IIIIIMLd I ion.

The riestest ii I iIitaIij/ed I iaisceiic I* p rlc uleitle[II, doii Ipe \ I these dta, 11a I'M "i Ill p111lItICIetIt I It,- Ijin IIiidei i i rqIreS hi gher P petoinantce I h11i.it I'I" ler Idata1 IN 'IelitsI

Audio Channel Peripherals

T\ti notable input uIutpuIt dI.-i itCeS tns beinig des duoped hr acqui te at tL 1CIIle smallI da.ta lelit 1,1l1( .tltesecure s-nice terminal. These pertipherals initerface \,il ri adio itrat'IsC l-s .at the audit) chattnIte .11d (11ie01eLi.include a %oice channel motdein i \hich puts petitrInaiIC IeqCtrlttIIV ts C1tn thre Irtsei

Handheld Data Terminals

Hanidheld triasatsbtltl. o cexteeupet IIttIIIIII10((WW olperato~rs. The\ alliisr ot I-line comnpolstitin attd edit I ug hetntc trarintisi-iot at teleus p\ Pr (ur1 t1111atC ,SI utuiplC

ref-quettrI shilt ke\ ig FSK I or- phase ,lilt t kes i g WlS K tittishfat inti te IC I Npical. Fiet Iiiiduftlat iii. silitaute. antddispla\ complete t heirI capahilit ies. Somne cinx eiIt lii alpltatitttic tit Nits elide10-S COI IIIIsbCIIit sttsqtet M Ii. si dedetmtdulation. Otie geticerates a miap I tilltsi a plaiua dispaI itrnid. Mus t use at in Iiatr tII nI IIetIIIatte-ti p\i. te Iet % PCkey board but une uses it-i-s allied al phltUtItrI ke slatnd ahit t111 cLit Ithl ed hi Ile IitIi li if e hoi ldinig hantd. Figit I e6 il lust rates rept-eseittti etilCnuItis1. anid cititecialt Ittdvls.

The develtipitetit ilt appi pitte de(Ic itk il Ic IitI tie I ossa Id, si1ltil Iti ig iutitital kI PittsCtISLt' Splc ILI tIstIggeSt s dlie rseI po ssi hi I It ks . Thet ShI des OWfQk[ RTYI tIes hi~ aid %i as des itgned (iii 1878 t spec it i i a I\ it I t I pt [lstatid asnid nchanical kes janlting. 'Fhe el tic lent . Cirakl, hIC srd,,m nsla' hc mitre appiloplile Ii rlitttekcshuat-ds. Scroullinig display keibtiards. i Ich are cititi itIgetIIit utL digrai. it uigtaui. oiriller ati tital Pt ihabilit tes antdl shift keys, seem lkel\ candidates t1l edceII the ntumtber ot Less.

Data s'u stems reqhuiririg fiast s~ iclioiiatioitatid hois t iiautsttljiitssstm require last aultotilt~ic Ile-clint nil lf-Oand autittitatic: gitlt Co-ntro (AGOt Iii addition t, litteat phasecllitsi., slela\ or- hiss t itugilg nic

. hamtnil i tring.

( Secure VoiceThe UnitIed States has, %% rked ilissi ais Secur 1 s1 %ic OLCl(InIIItitI 1icatonts s% stens t 2tt searsN. lier pillpI atS

included 2400 hitsN per- second (bh s% siciderciitupet itIiont, arid Ithe des eliipmntetttit i% Irel Ittc attd H1 F tmodeimt designedtut interlace with Ci.'neptil desii~kcs. The qutalit ot the t tautstuitted snice anid the clist tit adding three: majolraddititonal cnt11pOIFItnS (digital s nice de5 ci. mondemu. and ScCtrits des Let 10 raiot I.-ItIItIahs cftid [ltil jtit

acquiritiga gent-ral purpiiwecapahilit% untI iss o The iess linear peiti tan-i-hgtt iisilt ~ithtesiith utnenat ipeitgc ah i~inone package, is a s igiticant itisptow ci.

ifFtntidemis fillr high Speed dat a Such as 2401) Iis Ii git i/Ci.,iLh L i~.hv i l ~~ s d iuItpet ti.S uaI icarti- irigiller-entiilphas.e shilt ke i ng. Serial data intideiiiS pi iisiiie ecntiiical set- icellst er s% it elines: hut. tinl [IFradio i setsrks. iuiltipath di.las uSutallk iLattSes ittiersstnhnl iittetletettce. Coitscuitls 1. parllel llti.s has itigdluratini ttil ngei thanr the. i.-pcctedl mut spath dela% sait tintedcc, c% en thotughi pitll ICI Ithauuels hat\ C heiei] 11ti.'pensiwciuipleliienatin.Diildaapni'iigisitiitieshrlel. lutnltotPCi.-aht\ s iAsti.'ir.Ithelirtearii% reqouirenets in RE piiser atuipliti' ii.rbiithne(] %%i itheli high pi.ak-tii-aserag. pilsi.- at in Il parallel

tunis. ~legai~e sustet pelsirititeei.-ttttare tiltha iiitli ilittattt enlllope 11ttLit laiit lI tivits .

The conflict beeti mtaxiitruing pOster itutt atid itittiii/ing sell-induced iitirttidulatio noi istadd re.ssed in at nes% [IF mtotdern bi hartd clhippintg tire iensembl. itt tontres it) tedui.ce the peak amtrpl itude aid thentpirmsid inrgbaud I itiititing.AboutPq 5 i.Bol lt pak rIippiig piisidies thc.*best nseaJ ra JFII a nrui1i Ciitthlstese sploratris serial ttiodetttidscwliptti.'nt srtas pits ide per-lt iiiatici i ip ruts ciisiii.-~ r ihe pa tale I cIiiidetis

The s nicedLata mrti ne ied riot tmai ntaitt bettie.r thbain a I 1000 bit erroriL'Ftt ertiii.S ueL 1hai tii~.

import ant than oithe r dat a. "The Hi F nsodetti has been nptiriii/d I or, sendi~ i ng %ii ie dat O iE Hpit pagatiiit paitthat protect critical s nice d~ata %itith error-etirrection loigic.

The s 'vnehroniiai ion of mnodems and scui it dc% ices requi res set.eral steps %k hich niust he espe. talk I husthrI reception iril I not begin. Preamblescntririse s\ynchronization Signaling sequencies i% hi. h mas t-equ it-c 1 2 second~for transmission. The s%,nchronization time mhr.N he unpacted hkr. radio ALC and AGC ltme Constants aind hiautomaitic antenina-runing algoiithnts Ii some tratisceiwssdesigned foir push-in-tal k % ice conuni;ications.

10-4

rate. Both modern and analog-to-digital so)ns cesi~n %%.ill coint inue to reccis Cat tetion intt t lie %ear% tsr S lineS hec auwsccurc mice still sigini I cat I% deg radcs the ahilIit% to coinninicat-. espcciallI% uridutirinalI cotid jitt nxhi liteiodcren xli its thIresholdd perfo rimance. The prissi bi Ilit,% foss exists, hl twcser, that t he mtodern %is Il pet nt itic pit m

pci-I imc in the threshold pctt ritiane area.

NEW SYSTEMS

The svsiClS discnsscd hcloN dcscrihc nctxssrks xihich niax rcplace or snpplcment pcctciltuaii-The great majoril o itt F si scns operate in pinitto-point set\ ice or as part ol a Iitinitcd nctssiork ii tc rirta I,scr\ iced i a netwrirk control st at ion. Sistert I cqunc\ agi Ilit\ has heett limvited ix anitnnas, rrt ettna sit it in tg.and an ten ta tuniing. As the tit-\% auitiimat ic radii Isenter sets% ice. t he\i wIl enhance npcrat in nthe eNis i tig net ioksand wil h e capahic ol paiicipatiitg ti nmoie comiplex ncisurks through greater I rcqnenc\ IN lcihilIit% and thronghithc ahilit it) chonse al tcrnatiSc propagat ion pat Its and mnodc.

ICS-3

\as \ H F,serns at i tow ards I rcqnleiiC\ agilIit\ oit shiphoard plait nlts% ie rIc eculocationIl rirlcrikse IN .

dointi nanicoticern. The United Kitnadon ICS-3 pingrai it the Adm ilal i\ Snuit ace Weapons stahl i shittet I is cc toedb\ an attempt ix the LS Nas\ i to radicalIlox ie all sell -generatled comnpontents oft tie noise f loor. AIthbough thiss itiios is is indicatiscol a prohahle te\s H F net sorki ng capahiI it%. - 1(-3 l i ita i I\ ciihancsgion d s a c arid sk\siase tranlsimission, thirough rapid pr-opagat ion select ion aniddata hantuIlirig.

Figuri- 7 co nt Iasts ICS-3 arichItitec t-ce atnd its piredecessor Ftequncc agilIit% is ioht a ied h\ el I i nmating thecornplex iot tuited narrotis attd -ratisintitI tens aid rnIt iplexeis. I nstead, a h riadhard pumits aitpli l ci arnd allimahandles mnnlt iple i ndependeint s igntals. Receivers arc led h orn anl act xc atenna %S ItichI is smiall anrd I. iated IMiipiowd isoilation tront thle t ratnsmiting antenna. Cotiol is enhartced hsx comiputers.

The ICS-3 i-elated pirigrants spa%\s i ess hardss-atc oft 112siint irinars capahilIins - That Cqnipul I ti it.should enable networks capahile of coin rotlling link viii iissi astir niitiunile sell -iitiitIe deic e antd liii ice hix or herspect rnnt users.

SELCAL, Scanning, and Channel Ev'aluation

LargecSSB %itice netssrrks thfat ser i c ai rcraftI seek trianitinaic H F1irninn1fitcar ions. Fl iriinar iurrrrilchannrelmotrnitotrinig (an ontelrus additional airciew% dntm antd automatic addressing at the nihbile terinral \a a digitalpi-eambile (SELCAL are collateral inimosent Is ituiw heiing tested a long Si ithI a sr- Wiinrg IN sitr s% Itict pit. INs t ieIhest sit alteittat is c paths and I i equericiss as dete rmnred fix chantnel c% al nat ion. (haitriell scaltir Inrg Ifor nec t Upau it

uoriginted in V"IF equipmnent and is noss a\ ailahle I rn sex cral HF1 ntalirlactuiers. chtannrel Cs aittant i algirritrhillsar i-c nterr pritprietar.\ atid ar iUntde r Cont itoed d&s It ipntClut

Link qUal iii carl he assessed % ia the use ofttlen m mor nr i clasitl snchI as: signa I lci cl -si grta -tir- ii ris a lii.digital eriror detectioin, sorunder signal patartc Itinting arid tite delas Crririuiisl. antd ritenrrof t-ccii

sssitts.The requi remtet is it) lecrugnli ; a dlesiri-d signal arid it) late it ariong alter-narises xihichl ullt he illdiffereit ihands or frtomr alticritat sc paths or motde,. Signal ladtinrg arid niise s arnatiorts prCC I sde accurte sitrode-

chaitniel mieasuremnts itt less t hart ewrcal mnttes; quick mieasouremnts require usinrg ses eral I Irequetic-situlianerrusl to obtain t tcqncnlcv dis rsit\. Thtt-terefoe. a irteitir\ tahle is oitten tilte tial arhiner ofi chiannielselection. Orte schente gikes greater sseight it) ieceint measnremnirts.

Nio H-IF ltd s-irk s has b een a tmonnmted tising scantintg alt houglr demon si rat ins insol sing ses era I teinna Ishav-c shotwn hardware Ieasihilits - Anak sisoii large ncisimrks is lac-king. Clock, sarc iii i priipiisd sir that aft puss ihlccomiinatiioris arid li-eq uccics trna% need sc-anirting. Fi gnr i-8 sltouis a proiposed scatintg sihetie si Iich ItequLires 0.5;secound per- Irequenes -

A protgnosis tot the useit scaitiing Itiradaptitig to irrttsphericcoindit inns is that the ads antagesti autromraticalteinatise truting \ia the hest trequcnc artu path \% ill lie utili/ed in limnited iteissuks hut timted s-stetns %skillpirrtide access ki thin large netwrrks.

Imnplenenta im L SFLCA Uarid scanintg tech itiqes cart take pl as-c thirrogh i[he rerumite electrtical capahilissof nes i-eplacemnt t adios. Add-i n lund ihg furircralt teim inal sta is e artiipa ted tin iiitnwit ads ant ages it

the ground net ork emit il st at ionsm lie rec-ril ignted econitcal~ ls Lt imatel, prograins sUch as ICS-3 atissirmiore needs.

Packet Radio

In cointrast to SELCAL and scanning schenes. packet radiot is a comples ClnpUier data exchange telaxedamntirg ians Iinti-nI -sight I LOSI radio noii des. Au - I.-hand' ss Ste %%i ias s-hrosei t-i its I rcqttcnlc\ assigitirenasailahilits' and in consideratiotit exchaniging lOG)O-hit data packages in mnicroseconds. Tahle 2 its( hardxsare liorthis cooiperativ-c netis-ork des elipnit, . shich is a Iread,% i nfluentcinrg the inteirntatinal H F ci ttunumrits

Packet messages carr\ their irm itaddresses trialIsi the message it) seek a path through ses cal nodes. Thedominant nectwri-k crncert. is to as-itid rerlriad disasters. Mlessage lixipsate eliminatedb hplrritocols xihicli keept rac-k oI tuai -sitiln throtugh "tiers-"Os-rlitad is trnitii/ed hl\ -transfer poit" ttutitig arid i sluocking tile pa c

Jlo lyill ot ILL lics 1cily lyol'alc ntI'. I my~iy'I t., Ow~il " iclyIIl" it I ki ly l""i iixi ~/'.l

SNOTEL

Cl4Ll IIIlla ll (IiI 1)I Mc~io. I dI v ill' I iIcL 11,c n IIl Id. I ' l i I 1(1itl yIT,[111 i kes LI y ~ill'- y t .11 lI 11111- IlII yI'lI01 llE

lo h i/ clytil ymi .L IIc i l-u c 1 1 h 1111iltild %-l-1,0 Ild l tl 11d

lell i li-n ly' le~ 'lle o pI ip. lliolILIin" ~I' y111 'lyl'y'Ic itX lIyiy(I II"Iy ly.lLLl LLcIl Ll lll ll t l

% il y'o de I I LIel lly I I lill/intLI-, lll-ky'" I,~Ii iy illlly 1111 boX L- 1' JL l~~lllll U.LiiICELy IL %I I ML

,pJ i tdiy El HdCdjll 1, y Ii llIaLtI'. ;h i IIIpgl~l Xil~le y'y IIx C Il~ly L L'.ly Ilydi t y111 LlI' i1

lLI 11/ LI

A~lc. \lETl lily'bm propati ony' IFyiy'tiE iLi~ ' \.L jillIII-l btl~it lLl" \,em hI y'' hl ill illyIll , .i lily11

IllILEL ll il. F'i ll I CC ii IIIC.' hF XEE ii i i 'JktIy' Jy'~ 111CII I~LI.1Irt'' iio l 's thlil~ IltI lL k Jlel

o y'lL ll IS alil yiClc'011 l iiix L 11 i llyy yi\lllIl'l i~l -111CIIII y' Ill L plil l l f'i ileC~ y',\y' I I y lc IlI, ill I 1L 111I y

i(S-3 ljil ic s l00 'WIillCly 't Send i lily' ,PS lilyll i -t Ii 11 1 I llid iiy Ihc 1LIL ' fill

1 ~ \, I. lll lI'lIa id L t ll l l'IIl,

t'Ll11l111y'l L0%%iLit .illpTI.FI~LUi ,I lI ihl' I lL.' Si llkh' L iy 11 JI lI 1111 lLyb Llyl SIi llll. 1 'ILIL

a ~~IhL ri I %%oi in e ieIII-' l P ~ -- 11 I Il11

XI iti'haiti i F .illly'U, llll'. li t~ 1111 ll ilLiI( I'\ili O tdl \a v ndS m 11111' ~l'Llyy l ' I l ILIL S llI apl .i Ill , h I TOii .

1L I I ny'Hl l Cap hli \ I' ' [ToughIilCyE il ltil '.y'yl1, 111 01' 11ii11i.1111'

TLile npalcI o piLCSsuirs Ihil tie (I-llol IC lclllii oliii of pI L IT' y'iilvIlll LIi n,]\ i' Ile 111y'.'1 I Ii );).I1 I, Il

I~liode illy tile y'iilal ii uiitii c l'iiii li- Il:yl:Il I l i 1 d(I ly' TelI SNO' .'y el l) LL I1cTa t % n l oiNI

.S ai nuh\ ihy IT,] g p l iy'I '. I\ fgliClI I y'y'l I 'Xill l i gI t h I ldtITTj I I lgy'% Ill I T I gUlL iii " . y~llI

Iy'yyl 1\ Ciiltlldll L CC 1 a\ L Illi 011y'1idiyt Ii 5 i tll- illip cillIIL ITT y'\ Iill Iy li l"ill iIll'% Il lpai yli pI, IIt,

iCyy'I t''L alt' ollp l cti LIcd thii at p tielinei l I ofgl-iL I i~lllii~l Au an f yo\Iyiitji f PI, Lilfiel L L EyI.IJI ICiL o%'ld

a t' ill til pihas noil iisey'of lst hl iiiilyCl rf! l\Vi/l''l he p L(Ii C d l 1.1 OwI~~l s lloilw oo il Id l dll i I,\ -y111iy1ild

PILLillIC ihc U~ rC t pp dliakh iAtil iiill'lll'll'pli lbitll- 1111 of T hy yasy'sI 1111 i e\ lll i'y'yL'Ilt y' llylIllL 11'ci as.\

hin I d e L'CL d IiF an'L tnna ahrc nol-t 'iC aslie\% ho iic ' pr l itii all y'\y IL iii l l Soic i s t I- ulu i ji tiil

TC lCplLr prcLI silil p11X'r l luLL i sl Ct Li il~ir 3dBl lp lly iy\ The pil i l ,I El' In ing 111

Rive ri Dyihc Rang i nd NoiseFigur

Athyoiuhtlit\ r lieLliinc-lCag il st ck i i~iltilt latd x ldMILl nolg ~ise liiglLt ILileisL. lcULL 'all

aiiptci Il ed 11 I iiI IllanI i I ii litci't ilhxys x i y y'yihj clll \aatlxI p the tII I d Idc[ iilj t'F hpx h'oll'I'tincreaws inimpo-IF ncL LIit Ltilh .ljill an de llljsC of igumanhlted~r iCICClboiilldAtpi \CF 1llt' yjiidldylCi/'

illFiu '~I h lI~sC icl ose. i 1111 ilil 'dudto nlr~lp nI p 'fiIL 2nidhiti~hi pI hIi C IiU'II iadt'10 Fill CIhii10 ctd B gihtti silhadii ng ithapaht In eker ial-n lilet'sCioni all1 rent SicpboardsaIiu' tell yi'lidt.

paillriu tan hy'Ipdt anteas ilead tiiiiiniicl iolei I ilt'it'ric' su initclI luI inn ihc sanls tqtCl

s Otacie hps ) iil- U sed.~i Thes hih~iaproche ilsli l iC le Liese t' all\c o %\a~dllldhi'l'lidinal t'oise lt'otiL C assumptio lis in'Id o'ni ten \\Lallh scenarI .ioh 'yI inxii'L' groun %%m 1 io'g tioid' iand'p'' iii osp' Ihy' i

abiysorp'io illclyClp)11 pti tilngfo ise pssii Anoitrappioch ris lipihL enhohna.(L 1(s'igiit i ildl

hlihii inIt'y't of~ tiClIie ald I) use~y liy' appi%%pialt nidcbi gatptiinn. pali pgalior idli~L nuwt' aloibee

Frequency Synthesizers

Tih ii kro indsbl i r .itc siu c r a. c.ii% %11ite..v pefli lk idt tile ok l" c1.jolt 11 lii. iil Ani' fICI L tt 'l . 1111

11121111 % 1 k op igH n e sC eflt 1 111 il CIIII' h % 1II 1C I

(N tAI Iit.1 A hI gh c1. 1 1[I 1pc 11r L IS pI A (1 I i1'' 1.1111 \1 I I 1111 I A Is ihc I 1.01i I *[N I' IdI haC I he A \o lughI 11111AI I 11.11 Al 1 4L-

l .Iilles Iliifiltl ase)h 1111) hJrll.! I J1D~ jV1 ll I1.1 pIl tI aIg AI "it IdluIlc Is tItC II l Il dl '1 . a ail ~ \IA\ I th l aIcelatillgcail asllphill li i I~t. ll lalii .IIhgh. dil. IlI -1ll~ IllCI, nill i~cs Idilc~ 1Th1s Lm,1111l1 io llls oi ~ e a ls i t11

Ai I 1NIII I h1.' 11L p0 pnLi -C.pih I C loIIlS b iilt I il OI1I.cP Illi t i lilt \II1141p, \\ll he l l IifI I ti21111411 I\ al lit 1.1p11-' 12 ld s ailN I I

1.aphl%' on oNlschinI ofI\dl 1 AI,,I/ hilcc l C 0t. Ch1 .rchv II ili ltitti PI 1.IIkI 11 11 C/C1 % 112. 1 V )ItNC . p

ignId IlC IllV IllR 111ii ill it r a lLIg 11441 - 11111Pf ti licip -11 1 11 15IlI all .. An l[ i a L.I 1 i 11, SP 11i r I -111c s Igl il11111 C, pI\ 1lllil-ii12d PA hi, 11 Use ml 1.\ tll l III sip JI.TOICII \% [lits I Iiulti 1.1 ti1l Te l d 2 ilc-iit n 111 hi' )NeSA 5'I sILII

Ia pi lelitpom no1101i I ll. pf11lc AdC1 c ii~l, I% ar 1.elc I had lnwr m0 scil I'hlngh Lis% "\,.I on.111l .l it lc1 i I I I,5 I gU 11 m4 i.hn'.i C i 110\\ d ig I111 11hic I 11 o l I i 41115 IM MI aI LM l .1 111.112* Lilt15 I. I fII ) II 11t I I ( 1 1111 Ii g 't. -I h

Iheampli IiredsignalI at IId Iii'.I ing a luttcI pl%%eIC ccItToll signalI. At the picesent I title. SO d1 B ILIPT sII I i t11 1i1totile. thi I d-iotierI produtit hIs hi cn CIobtiti ed tin SttO W peals cit tIcttv po%%crtPllPiat Ni II, N. t" t I )t.Iic IL v ,pii"ithi% 20t diB "t 30M NID. tnt1 ifin IaCIc I i'hiiwNc Is t% ies, tI rn (1 , I . m ftil v L IIIleft I periI I I i I ILC% it I IIl

III 1ditI.i 111 '14) i.'I 2 e t LI til, illjnli ilttm .%% tlhI ttban Ilis call Ilisittl (a probhlemt. parl ittlal I% Ilus 11tt

tutu hi 11eqirel 12(luiatill itt I ld tisllClIalt1dectr ICC ltctc % It t\idla ltulSC Iso1m flic- PA 11121tcltcsIci 1.121II% \%titl

%%Ii dlxi hut I Signials at Itiw'I ccici L.

X% iidebaiidl ailphlt i apptiuacL 1 uss '4(1 lixiltl ItoCliffs ill dissipate u[citet edlitleIT li dtuil'? .!a

a jTiauiuii atc xiiit igi cihu ii'ita alticE :Iiciti-At appearsollplliefi I uittctl C111hi'.11iuiinsot lc ut bCliiiSutiuuiiti l ioiikt. titA fill'. Il it refptit ettiMCMl hillllt p iCStia l t L1i[I' I TTiiuic l itH M L tdt 'ltt li 'I te

allilicit a t ila hilclit beef)i cIJt 12jul1 lainit i'i. hC 111 111%111-)IIL 11CI

k ll il ta elVI I IN i A Mottif.Tn. I t~ijl v\lli .ii 7,u dBii0t ofa I PI *iitu Iip Ih t IIIIlIIIt' L titn li lcl(\C I- eitan Ii . 1111111111 CitNl X Idtt,WitlI lISt .1\ tiilhlk pii I(i aIII i l c It TIliS Tit sIppcsil C Ii litlill t Stljtctiiiuhtll l i

11titsiat 11Iloc I u iteit ldtit t i le~ t he pIltil~ P u t Ulilki iii titLCVtIMa Wiut 0I pett iiil-)Iti 111ittilutl IMtt P A i1t h It11I lrpIit Tll lI

Wideband Ante~nna Systems

athC 1 11 lii it,11 11,- C II

h 11 -0c1% l L nialil.IV n of[% ic1i' O)Ih10l tac that ll Ci ainis arcll\ ' Ici ll b\azh t ll'~u cIi iliital pt I tI," (MMi..AL ll a ti c iils liii itti ,it loltis cLu\Lpi'u % Cg pidii ciiitU l.l C h o lK~ ll_ Io ~ lIk [l CII11 1,1CkC l T

adl1uit xvIt l l t uNt tl' ige ttii ocuii. 11CIll 10klli\lul WltI LIll ITuutt M LAI ictit W ii~il sii. 11,ti l e '.ts \t 1111C \\I'll

-1ii h'er thll ac il gaine chatacte it isli'li 1ut KI the TIZ fip lil ilediIT) ciltIc 111 oldippiittci l t tut 111.x p \% tt Ill~t lltittlldlie ue t exel i iin m til v %t nulls.c ilkTa SI, I mte lililillte c a l le, ll a gaIIbcll itt tcIlcS II(l cv ill Tit a ao

I litlti iii I leil'li antLId cb\ a11iijitit l igh lh i s aitis 'it iiiC s1i'rl itlehelsIoittt tait expctedAImik "mnflltc tatLI\ CLI Li 111 a l(l el t %:iTTi It Salla n op l oltu n ile - ii d ist iii t LqINCtI lt iiilII iiisdt i l tit tiile~ 11sii

l~Thel imigti-tclui tileuexhiit giood eli aillt aile paI-is cld \lA th ~ ih i' iuig IlI II ifithc aititita

g IIt caltI u. al I t I~ Ion Sat Idchs, Pv pIcial at), F i c10 h T li'.I i ttlta u i tI igl tll Suidta tuui hIifI atC I t it' I t ii MCII0It il I C I.tLI'tiLitd1 ttpiiC(UTIL MII C I% it (ion11 trcaultla-g path I huts \ Y V 'lId~bIIl\ t a xlrdA~~lI

theialls \%diatltl the t\%r/iiitlllt illai 11tL 4t 111eilcI'sIIittoleitl hct'lcnc tlt oI iItanit iOIsItei olgI iti011igure 17. tl 0CCitiu (11 1;;1k2 I alinlca spie ct i. thctc(hiiuii~tI bohTh l arte otsietle Lmu hiirlul at atuiI vless.tklai I tgllt anda lull at. lo tttiltlatl ll illil pititicrehm ptle it hittheelalgiialsttatc ul

iisi-epuiiatsdl fititt ~tthe. hoio alkpii d imct dtdcn ti~s ialltn atti acciidli tt hissaic 111, depmtltit to

Ot hir biuoadba tud all Iittlas av ii'i istted ill Figuic- lIS. Recottl apptioiac In1c1 lde I uttedilap alilittas.1tuhich ititti ituallt litiouui lt it e\ 1lifig. 1igute I 14 Shi(\t ile Per Il tIM11Itc iit a tuItwiCI-tlaip attlettllm

dci liilpeii lot- lCS-1 A i tlage Stading l\tii tat i( tNS VI less I thani 13 I i Tc i mi ct\ tangi' ii ll 0 Il/It iobt alne!dl at elelic iei'e I 400.

A Simtiple. elect lical i -thurt mothipi leitiducit ck lo adied ill the tttiddIie tihits imIliptiti ciii itea eth ll\ if'tciis i esiml tel loaded at the hate. higt ive 21) shim Itit-h s uiilnminlci ilupiltme 121121 iin l antcnt l tdil hitgh

Cominin i t ntenna liadinlg alnid a tli motilpi i p11 duces the Smith chliart perlti ittattti hoit i fit nt Egul ic 2 IConisderlahle I leedlm is at a i lahle liltia til del eloping i ntiit ii hel wii i nas hat ng acccp ahtbi loadingprouperties.

1Frequellc~l-agile allutetl coler p1, Isriat\ not hb' Iteia tt I tcqUetti hioppedi c im-it Tie h.ItIII\LI lil hiiciuuplCI- IsmaN hie applriit lah..'h I 3( ii t hetelil tI lquetli t - oppitig i t hin thle haud\Idth hIs apiplipt-talt iti Ill:ioniispherc-i piopagalioil. Rcesiti e llllla louaing tall) ii11ltpti the hanciiuiths a matlahle. 'Ntcutiiel'. . si etdfleilldts caln he uste.

Processors

Di ia o nI(Ii Niiii% N IIN IlA LC fl Il ? 4)1 I\NL11I 111II H I I -'e ]I

automatLicci 'Litciitiilc is, t inn ti CkJ1lL esa l'c I 11iii cl ktlit i:d tiap ai atI' %. BA I 11'. tic~: i it lirtgtiaIii tokcil IS32 Mipcktd ofFli 48 bIs Lilt' tilt' tuthld Iiiit'(111I'i Itt' Kt IdedI I cie tti t iic tlt'di tiiiinn IBAS1CIII \C I LLingulage d (Illtel t'l i' -lnt t11 )CIIl( dll I 11- Itii iiirag \C I -u 'Lcliiic Lit' iit''a M , Ca'1 I ilQi: ntc'

Onl t su heiI ti on - esIoLil ItOal1I )1 Ii (t it Ii c t Il I i I ithIif lclt"I ilie la\Li t ici I hct c cd ti i I 1 c '. I'

usi t-aciientra ciiicklc pisnox d e l e ti i''' and t~piult lood. ' t tui ctpu ith-a tBuSK ci fl iiii'it'la u M LJ'Va Icttli tim Lliiii d Isi Ei'ui F h T88 fl t ifii it IC(lC\I C aI i )I Ci uIcui i it'tiN It't' elh t Iii' it -11 iu o ll t ei] I n "aittli- t' aili I t lBAI(u

tilt iriUuImCniS. A I hitaIjuIniC 1 II Is lit t~t I il itt' Ili tCtt i(ii lia iittt It aI at~ i itt LI1 -k- Oii t11 wh Isack ira' at 1.

i Sui ce pe i lt Ii0 C iiil'i Lu11111 1u andiIt.iit i tilt' lI'ill/ clii it'\ III t Il'M nI 1111C Ililt ' 22.itLlletc -1C k1,1\

M,01rlla )l)i)pinai ~l \% fI\Ies% tI,tii IUkM11TI~it plii1l-littitt1a tispiluu ki oIt'~ tIa 2~l I Fit- 111ht1 1\ ttuut''p 1it1 iti pat.1h1

hiur d siloru o 3 mi ife tut'sii, an i'Uhbitliiliii, vli kciitit d i c iwt'tct I it't\ I It 11 lug iat'In L''l _d t' -- 1 tint a 'tt \

p Ro i ifit- cqonipituing tic\iCiuil ictiV tiluiittt hi~k liil r c iu \ipu i etLU \ l'li Iiitiic~ ii0C.1 isit' i I' ci ,i

d Epend lii i c h i i kiii i iefit ciiici Lilt ' ill t-ip'iiit' li I i IT' V iiit I iilli t it isae hig ttieip'ltl itt

tom111lpuiitiSIni IitI CLIC1c sie lI tI \C Th iii ''I tt' s uii t-i Itiu Nip Ce MMilti iLIIti I~itl t'Il'ui' 10lt' M II L i ti it 01111 ivl t

b\Nl9C~ ( C ul\il1111 ie ( I111 t, lliI IO -O1 de I ~ ik o ,A iI t lll'iik

Table 1. Typical Receiher Performiance

seii.ItI k Ii ) 0:pl hit I OCIB Is+ \I \ ilA 2 4 1,11/

Lin aI c I Ii -42)) dliii ih I Il-4 4d ttt IIIL*ICic t I M 2 clqtil i,tic, it;() kI .ind ' k IIl i I I iii I I Ic I4

RcIpon u.x8 IBippic-'ion ,I Ionc 10 k I I/ I tc ii 2. ki I / an

Band paxx Tinic[)Vla4 Ic'. thiii 0~ ii, ,it iatii,in bctccii (00)) if/ aind 2700 H/,

Contio1 All iciootcd it. RS-2 12(. I EEE 488 wv IR 1) pial Ic!

Biiill-ii- I et Funi i10i1 IV\. Cl

Table 2. Packet Radio Evolution

Expcimnti itiiproxe Vit alue Fog 14%(,lit

Pac Oct Radii)i Pit, lic Radii, Pa, kct Rail I(, Pac kit Radii(EMR tiPRI )VPRj [['PRi

lMcvcOPIociL- 1974-1977 I 97ei-179 19s0-1982 1481-I1

Numbecr 28 27 is8

Ne~t Timing A,\ iichionoux A,\ inchii,u Ax,\ niiiiiii Ax,\ it,~ h immiu

['N Code Fixcd Fi..cd [i~cd DES Di ici

E:DAC CRC C( ( RC URC FEC

Proccxxiir IMP[-16 TI-991)0 TI -49)) MC"800-1.ike

Memor% (hb% test 7 K ItK 22 K 12-t4 K

Size lit)t 1.1 1.7 1 0 0. 1

Weight (Ib) 40 ;)) l0 12

Prime Powcve (WI 40)) [00 [00 25

RF Band: 1710-185~0 M[], XMIT Pii'.'cr: [0 B iid%%' tdth: 20 Mll/

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PROPAGATION II. PROBLEMS IN hF PROPAGATION

by

F V Thrane

Norwegian Defence Research EstablishmentP 0 Box 25, N-2007 Kjeller, Norway

ABSTRACT

The ionosphere is not a perfect reflector for HF-waves, and the lecture will review some of theresulting propagation problems. Some of these are encountered during undisturbed ionospheric con-ditions, such as multipath reflections, but most problems are associated with geophysical disturbances.Solar flares and associated magnetic storms cause absorption, low MUF (Maximum Useable Frenuencry,scatter due to irreqularities etc. The ionosphere is particularly variable in high latitudes whereauroral phenomena influence the reflecting properties of the ionospheric layers. The lecture discussesthe presently available short term forecasting technioues, and it also deals with nossihle ways of mini-mizinq the effects of ionospheric disturbances, such as path and time diversity, the use of early war-ninqs, and back-up systems.

1. INIRODUCTION AND OUTLINF

The ionosphere is by no means a perfect mirror for HF-radio waves, and the purpose Of toe presentlecture is to discuss some of the most important propagation related problems in HF communicati.n. Someof these problems are caused by the inherent properties of the undisturbed normal ionosphere and itsvariations in time and space. Other problems are related to disturbances in the ionosphere causingirreqular and often sudden chanoes of the propagation medium from its normal state. The le-t,re willdeal with these problems separately. The qeophvsical disturbances are most freouent ad s%ere in1 ilhlatitudes, and a special section will discuss high latitude propagation.

In the companion lecture we have disctssed the loon term predictions of monthly mean ionosphpricparameters. There is a need for short term forecasts for periods of days, hours, or even minutes, toallow the operator to adapt to rapidly changing conditions. Some techninues for short term forecastswill be discussed. Finally, discussion will center on the possibilities of avoiding or minimizing thepropagation problems.

2. PROPAGATION PROHIFMS XJRING NORMAl , )NDISTtRBFD inNOSPHFRIC MNDjIlT1

In this section we shall discuss some propagation problems encountered to the normal, ,odivf,4rteionosphere. The distinction between undisturbed and disturbed conditions is bound to be somewhatarbitrary. For the purposes of our discussion, however, the ionosphere is undisturbed, or nnrmal, whenno distinct geophysical events, such as solar flares, or magnetic storms can be identified. Under sunSconditions, the critical frequencies, the laver heights and the ionospheric absorpt ion show rno largedeviations from the monthly mean values, as predicted by the ionnspherin models discussed in the rn-paninn lecture.

2.1 Multipath propagation

Figure 1 illustrates a typical situation in which several propagation Modes exist simultan-usiv.and the received signal is a vector sum of electromagnetic waves arriving at the receiver fr - tfi ere, tangles, with different time delays, amplitudes and polarizations. The result may h severe distortionof the signal, for example deep and rapid fading. Such fading may nccor because the differenit signalpaths change with time in different ways. In order to detect the resultant sqnal ahrive the backgro,..',noise, a larger transmitter power may be needed than in the ahsence of mui ipath propagation. F re-quency allocation in the HF band is based on a 3 kHz channel spacing. Within a 3 IH, bandwidth thefading may not be correlated at different frequencies. This selective fading can produce distnrtion ifthe carrier wave fades to a level below the side bands. Selective fadinq in a I kHz bandwidth channeloccurs when the time delay between different paths exceeds 500 us, that is when the distance in pathlength for the modes exceeds 150 km.

Different modulation techniques are affected in different ways by mltipath fading. Analoguevoice transmissions are relatively insensitive to selective fading, whereas digital data transmission isstrongly affected by fadinq, even for time delay differences as short as 50 vs (path length differenceof 15 km).

Fading due to interference between different rays freouently occurs near the skip distance, that is whenthe transmission frequency is near the MUF of the circuit. As discussed in the companion lecture, highand low angle rays tend to converge near the skip distance. Fading may also he caused by the inter-ference of ordinary and extraordinary maqnetnionic components of the wave, since these components followdifferent paths through the ionosphere. Fiqure 2 shows an oblique incidence ionogram in which the delaytime over the path is recorded versus frequency. the situation is complex with many modes present.Fiqure 3 illustrates a similar situation as observed at one frequency (8 MH).

2.2 f ffects of ionospheric tilts

The models described in the companion lecture taismet -hat the io-,sphelcr !atr, are ou r-1lle

the earth's surface. Tilts, that is horizontal gradients in the electron den-', are, how-ver.

important for radio wave propaqation. large scale horizontal nradients, such as the dti-niQht 'r.n-rition reion near the terminator, ma' cause deviations of the ray path from the treat circle pa'', t--

aeen transmitter and receiver, with corresponding chanqes in signal charactPristics. Similar :,roh4' -A

are also encountered for propagation alonq the auroral zone. Sich propaqation is difficult tn ro e),heause the effects depend stronqlv on path geometry and herause the ionosphere changoes rapiul,1 will,time. Tilts with medium scales 'a few hundred kilnmeters' mist also he considered as a normal 'ea'r'

of the ionosphere. Such horizontal gradients are associated with travelling innospheric dlsturhi'ostI[)sY. these disturbances have wavelike structures with periods of the order of tn-in minutes, a,-

cause focusinq and defocusinq of the radio waves. Finure 4 shows an example of a stroq Tin infleni,the virtual heiqht of reflection in the F-laver Gfeorqes. th7'. Rbttger t'7R' has studliel the

ocrureice rate of tIl s in the ekiatorial reqion. Figure ' shows the results, which indicate the pre-sence of such phenomena 805% of the observation time dirinq certain periods. Pice 14'6' has a-ury'

the dirertion-of-arrival-errors at HF for a path throug~h the aurnral zone. F iqure f shows ari i p! -r

the distrihutinn of measured bearings. The medium scale tilts will in geoneral cause fadinq and dit ur-tin of the siqnals.

2.S the effects of irregilarities

In our previous discussion we have implictlv assumed that the innoaphere is smooth over the are-a'the first Fresnel ,oneu which reflects the wave. tn prartice the electron density may have small scalestructures both in time and space, superimposed on the general background, these irreqularities at as

scatterers of the incident radio wave, and thev may drift a-ross the heam of the transmitter. Theeffect of radio wave reflection from an irreoular ionosphere is that as illustrated in Flure 7' the

received wave appears to the observer to come from an extended area, rather than from a point, the

ionosphere will act as a diffracting screen, protectino a mering, diffraction pattern rno to the earth'ssurface, the observed signal amplitude will fluctuate rapidly, and the fading will hav certain sta-tistical characteristics which depend upon the properties of the screen. If the ionospheric screen is

random so that none of the individually reflected wavelets dominate, the amplitude will have a Pavleigh,

asmmetric, probability distribution function, as shown in fiqure 8. If, however, the received signalhas a strong steady component from a mirror-like reflection, and in addition weak random components from

irreqularities, a more symmetric "Rice" distribution will he observed as indicated in the figure. Roth

types of distributions are observed in practice, and a knowledge of the statistical properties of the

siqnal amplitude and phase is important for the determination of required sional-to-noise ratio.

Ionospheric irregularities occur in all lavers. In the F-laver innomonde recordinos may show"spread F", that is diffuse traces where the signal appears to be returned from a wide range of heiqhts.

Spread f occurs most often at freouencies near the critical frequency, in the niqht time ionosphere. It

is more common in high latitudes and near the equator than in middle latitudes.

trreqularities in the F-reqion is often associated with sporadic f, which will he discussed in the

next subsection. Relow the F-reqion HF signals may be scattered from irreqular structures. Some of

these are caused by meteors, and this type of scatter will he discussed in Sect ion 6.

2.4 Sporadic

In addition to the regular ionospheric lavers there are several transient or irregular layers, of

which the sporsid f-laver is the most important. Althougih this Iecture deals with problems in HF-propagation, it should be pointed out that efficient use of sporadic F reflpections may improve Htransmissions.

Sporadic f ' f,

occurs at heights between o and 120 km, as a laser which may have much hiqher cri-

tiral rregiencv than the reqular F-laver. Sometimes the lonoqram indicates that the f5-layr is thick

and opaque with a well defined maximum, at other times the laver may he thin, patchy and partly

transparent, go that hither layers are observed throuth the Eq. The Fs has different characteristics indifferent latitudinal zones, and there may he several physical mechanisms governing the behaviour ofthese layers. It is believed that windshears in the neutral air, acting on the f-region plasma can

create sporadic F-lasers It'himonas & Axford 1966).

The sporadic f-laver is a problem in Hf-communications because of its irregular and 'as vet1

unpredictable behaviour.

The observed statistical occurence rate of Sporadic F is included in current prediction srhemps

for HF-communications such as IONCAP, (see companion lecture). fioure 9 shows the statistics of 1. withcritical frequency FFt > S 44z. As will be soen, F, is a night time phenomenon in the auroral zone, and

a daytime phenomenon in the equatorial zone. At middle latitudes there Is a stronq seasonal variation

with maxima near the eguinoxes.

tine of the most important effects of Fi on Hf propagation is the Screening effect. As illustrated

in Figure 10, the sudden orcurence of an FS

laver can prevent the sirnal from reachinq the f-Rlaver, andthus limit the range of the transmission. The patchy and irregular structure of an [-laver ma intro-

duce rapid fading, as discussed in the previous section.

p I f

2.5 Non-linear effects in the ionosphere

The ionosphere is a non-linear plasma, that is, a radio wave travelling through the medium changrq;the properties of the plasma, so that the wave influences its own propagation as well as the pronagationof other waves travelling through the same region. The most important non-linear process, from the pointof view of propagation, is most easily understood by considering the theory for the refractive index if

a radin wave in a plasma. The complex refractive index has real and imaginary narts

n z i(Nex)-iy)Nev)

which both depend upon the electron density Ne and on the collision freouency v of an electron withneutral molecules and ions. In the companion lecture we discussed how the electromagnetic energv

carried by the wave is lost to thermal enerqv in the plasma through the collision process. The colli-

sion frequency v is proportional to thermal enerqy, that is to the temperature of the gas, and thus

absorption of a radio wave leads to larger collision freguency, which in turn leads to greater absorp-tion. This self-modulation max distort a radio signal, and may be important for signals from very

powerful transmitters. Cross modulation of signals in the ionosphere was first reported h Tellegen(1933) who had observed that a transmission from Reromiinster in Switzerland (650 kHz), received in theNetherlands, was modulated hv the signal from the powerful radio station in Luxemhourg 252 kHz'. The

effect is often called the Luxembourg effect, and has been shown to occur maints in the lower ionosphere

(F- and D-reqion) when the collision frequency v is large. The deuree of self- or cross-modulationdepends strongly upon transmitter power and upon freouencv, and may be of the order of 1-10 for wavesnear 2 Mlz and transmitter powers of 10-100 kW. (See for example Davies 1969, and articles in AGARD 1P38 1974). Self-modulation may render an increase in transmitter power selfdefeatino because it introdu-ces an effective transmission loss 'Meqill 1965).

Non-linear effects in the ionosphere have been studied studied extensivelv hv many wcrkers, andthe reader is referred to AGARD CP 138 and references therein for further informatinn.

3 PROtPAGAIION PROBLEMS ASSOCIATED WITH GFOPHYSICA1 pI/STURBANVFS

The reflecting and absorbing properties of the ionosphere often show deviations, from the regulardiurnal and seasonal changes, that can be associated with geophysical disturbances.

These disturbances

fall into two classes i) those directly associated with solar flares which eject energetic radiation inthe form of ultraviolet radiation, X-rays and particle radiation towards the earth, and ii) those asn-ciated with changes in the structure and circulation of the earth's neutral atmosphere. Disturbances inthe first class are best understood, and their causes and effects have been studipd since the discoveryof the ionosphere. The possible importance of the secnnd class of disturbance has been realized only in

fairly recent years, but the "weather" systems in the upper atmosphere and their relation to loweratmosphere weather and climate are still poorly mapped. The physical mechanisms are not well

understood.

Geophysical disturbances and their effects upon the propagation medium have been reviewed hvThrane (1979) aid by Thrane et al (1979), and in this lecture only a very brief review of the Hr-propagation problems encountered during such disturbances will he given. There are mans wavys ofclassifvin the disturbances, none of them very satisfactory, Table I lists some disturbances whic

h-

have important propagation effects.

fntrv a) in the table represents the initial effects of a solar flare caused by wlectrnmagneticradiation. Fotries b) to e' repr 'sent delayed flare effects, due to energetic particles entering thupper atmosphere. These effects are all part of the verv complos seg uree of ;,henomena called a marine-tic storm. fntries f) and W% are disturbances which may be caused hy particle precipitation, huttogether with entry h they mav also belong to class ii) discussed above, that Is they may he triggpredby changes in the neutral atmosphere.

In this sectinn we shall dapl with some propsqainn distrrhancea in middle and low latitudes. vid

discuss high latitude problems sepnarately in the next section.

1.1 Sudden [onospheric DistRrbances -SI0'

A sudden hurqt of X-rays and IV radiatinn from a solar flare will cause incroasel electron ,'rrr 'lin the lower ionosphere, and "black-out" gf HF-cvrruits may occur over the entire sunlit hemispher,. Ifthe black-out is not complete, the signal may stiffer sudden frPguencx shifts and phase changes, d,e , t asudden lowering of the reflection point in the ionosphere. Although the disturbance is normallv shorf-lived (- I hr) it may cause serious disruption of traffic, and beratise of its sudden and unexpectedonset, may cause the operator to search for technical faults in his system.

1.2 Magnetic storms

During such disturbances currents flowing in the ionosphere cause chanoes in the earth's naqnet i-field. In our cotext the most important mid-latitude effect of a magnetic stnrm is the doecrease, ofthe maximum electron density Nem

2F in the F-Layer. Such decreases lead, of course, to decrease of the

MIFs. Storms are also oft -n associated with absorption, due to influx of precipitating particles atmiddle and high latitudes. The absorption enhancements increase the LUFs, and the result is a

narrowing of the frequency range available over an affected circuit. Figure 11 shows typical changes inNenF2 in different latitudinal zones (Matsushita 1959). Strong and erratic time variations in t cancause major communication problems. Roth MI1F variations and storm associated absorption 'aee entries dand c) in Table 1) are strongest and most likely in latitudes above 400O50

.

114

3.1 Winter anomaly in ionospheric absorption

At middle latitudes 1350-600t, ionospheric radio wave absorntion in winter doem not follow the

simple solar zenith anqle dependence to be expected from the averaqed summer observations. The qeneralbackqround of winter absorption is enhanced relative to summer values at the same solar zenith ani,

and in addition days or qrnups of days occur in winter when HF-absorption is qreatlv enhanced above this

barkqround. The consequences for communication can be serious, since absorption vales of 60 d9 in

excess of normal may occur on W and HF-circuits. fioure 12 shows typical values of ahorption durrlno o

winter period %Schmentek, 1971). The horizontal scales of the disturbed rpqions are of the order of

1000 km, and the maqnitude and frequency of absorption events increase with increasinq latitiude. It nowseems clear that the larqe and variable absorption in winter may he associated with

particle precipitation 1Sato 19t8, Manson 1981 and Sato lqRI) and that there also exists a

"metenroloqical type" winter anomaly. This type is associated with neutral atmosphere rirlatinn and

planetary waves, which throuqh creation of turbulent transport of minor constituents 'nitric oxide. Np'.

influences the ionization halance in the lower ionosphere (nffermann 1q82'. The physical models

suqqested to explain the "meteoroloqical type" anomaly are still crude, hut may point the way towards anunderstandinq of the propaqation effects of other dynamical phenomena, such as the stratospheric

warminq. Increases of 0-reqion electron densitites of a factor of up to in have been observed urino

stratospheric warmiqm. 'Relrose 1967, Rowe et al 1369'.

4. PROPAGATION PROIRLMS IN HIGH LATITUDES

Disturbances in hiqh latitudes merit special attention hera. P the simplicity and nubility of Hr-

communication equipment make this type of communication particularly useful in remote areas, and formobile units. This section will discuss the most important hiqh latitude dis

turbances and their effect

upon communication systems.

4.1 Polar cap absorption (PWA) events

After certain types of major flares the polar reqions are Illuminated hv hinh eueroy proton; ad

alpha particles which penetrate into the lower ionosphere and cause wide-spread and lont-lasting diusrur-

tions of HF-communication circuits. As seen from Table I such disturbancps 'to not occur often, hut themay last for periods of up to a week to ten days, and may cover the entire polar caps down to latitudes

of about 600. The absorption may he severe, up to 10-20 dA at 10 t44z has been observed. This means;

that 14F skywave communication svstems in the polar regions may be rendered completely useless for lon

periods durinq such events. This fact has to be faced both by military and sivilian users, and hatL-ipsystems should he available where necessary. Possible harkt-up systems will he discussed in Section y.

4.2 Auroral absorption

Aurnral phenomena are often associated with radio black-outs. While the visual aurora itself is

raused by soft electrons (energies 1-10 keV) the enhanced absorption is raused h electrons with

enerqies in excess of 10 keY penetratinq into the D-region. Figure 13 shows a map (if the statistiral

oc uurence rate of auroral absorption measured by rinmotery at 30 t4z. Note that the absnrption is

stron(test in the auroral zone and has a variation in maolnet ir time with a maximum in the early morninohoru., Fable 2 indicates the ratio between the oblique path absorption for a sional proanating in a gr

mote over a path of 450 km, and the riometer absorption at i0 41z.

Oblique path absorption (dR

Frequency Ratio =Mz Riometer absorption (dR at 30 MHz'

2. 51283. 80

8 22

1 7

Table 2 Approsimate relation between oblique incidence and rinmeter absorption

We note that auroral absorption may have severe consequences for radio circuits rrnsinn the auiroral

zone. Stronq auroral absorption is, however, often limited rewornphicallv to patches of a few hundredkilometers in extent, and the duration is typically 1 '2 to a few hours.

4.3 The hiqh latitude F- and F-reqion

The morpholoqv of the high latitude F- and F-reqion has been reviewed by Hunsucker '1979 . Roth

layers are characterized by qreat variability in time and space. Fiqurp 14 shows an exampl, of F-refgionelectron density variations durinq an smroral event. nurinq very brief periods the F-layer critical

Frequency is lip to 15 MHz, which means that for a t41F factor of S (see companion lect,,re the laver

could support 14IFs of more than 70 MHz. That the aurcoral F-laver sometimes ran support VHF-prnpaqt ionis supported by figure 15, which shows maximum observed freouencies over paths from rollpr Alaska tn

Greenland and Norway.

the i-reqion also shows horizontal gradients, of par!ticular interest Is the F-rplon trouQh, whichis a niQht time minimum In the variation of the F-laver critical freguencv with latitigde. The troughmarks a transition between the mid-latitude and high latitude ionosphere. Figure It Pesprszvannava et

at 1979' shows the variation of the foF2 'normalized' with latitude for all rnths dur ing 1q64. %Not e

the "wall" of ionization occurrinq poleward of the trouqh. This sharp gradient could cause rpftectinns

of radio waves, and result in deviations from proorwoat inn alono the qreat circle between cirr,it Tor-

minals.

Propagation in the auroral reqlons may introduce rapid fading. rioure 17 shows examples of fading

observed on an auroral and a mid-latitude path.

Note that the ionospheric models used for lonq term prediction purposes do not prnperly allow forthe variability in time and space of the hiqh latitude ionosphere, the data base is certainly tnade-

nuatp for detailed mdellin, and much more work is needed before usefujl models can be develouped.

4.4 Some results of HF-transmission tests at high latit ides

It may be of interest to demonstrate some of the characteristics of Ht-propagatinn in thedisturbed hiqh latitude region, by reporting on the results of some transmission tcsts made over two

cirrulits in Norva% tIhrane 1979

The purpose of the tests was to invetiqate the importance of frengPriec fleibiIti aro 'macediversity in and rnear the aurora] zone. Firiire IR shows the path geometry, The loon cath 12'fP vsnormally has its reflection point well south of the aiiroral zone. werwas the shorf natS, g- ii~n

iurl-idP the disturbed region. A simple digital test signal wa 'rursmitted on coir 'rcou(leroen 2.nnA.,, P.1 and 15 '41z over hoth circuits nao the error rate of the received sinlsla was re-r l for

seetcttime; of day ivid 5i''iO the f~ Itwanj rulso f11iv 1 1'ted intoprios win'Ii'errt e'0 .

auroral zone dintuirharirP, as masured hv a run-meter in the atirnral zonfe see fitre 1q . Inc rc'>ult"

from mreasurements; on the our freguvn-- nd rr over the two paths were rooP fe;' to ; a'olats a'sstems. Thus roatprtations were made for five ras

-s to fird:

a t he re Iiahi litv Wlien unty o e pat" and irole ' prrguiu are avail isoe t wn -aner, long ut't

'r '

h The -plisbi 1 itv when four freiuo'in An;! one oath Ar, am av ibIoe, lwavsuvir he cot e I 'c',two rase, ]niq aid short path

t he rpliabI It wt1 fwo iatths Aod fnur 'relies- iA; r1m A ov tle , ,ri tome;' 1r-i-g -1path at any time. Thris s;ti, irii simrlutes A roloy system In whirh a "'r'a, tr

run I to P via A. We have asnumnd o 11pm- rAltlo 1'ru'oo' I '1m -' t', A

IrtNO'Pt RIC QUI t I 1n4lllRA t tflItiNPtf 0~l IND I[ I 9{NI;

' fIt{ un0-n.? i/!

ri n.2-2 fP' I~ I 2 tfo

SN1i tRFttOtFVF 73% 51% 1%SHtIt PATH . 1H1)

Ft11 F Rt Ut11 WIt 78% 72% 37%

SHORT PAtH (.5 41z)

SIstil F tilt 01tFN' 71% 71% 40%1 ONG; PATH R.1 W7z)

F IttR F R OIFNCI IfS 88% mtS%i nNP PAtH

' noIp FRft (lt 5t 901 89% 621

lIN PATH,)

Table 3 Peliability for different systems and for different degrees of ionospheric disturbance

Table I summarizes the results. We note that, particularly rtrinq disturbed conditiona, asubstantial improvement in circuit reliability may be ac'hieved by nwana of freguenc'y flesibiltt and

relaying, (that is space disersitv1.

Monthly means of the measurements have also been compared with monthly mean rellahilities pro-

dicted by three different prediction models, Applab Ill (Bradley tl7s', ItONrAP tI nv et at1 18?' andPludec4 ('IR 19781 (see also companion lecturer. Fiure 19 shows the results for the two paths tirinq

summer noon conditions. There are considerable differences between measurement and prediction, as well

as between the different predicion methods. There is a great need for mnre and more accurate measure-ments to provide a basis for improvements of the prediction methods.

S. S(ORT TERM FORECASTING TECHNIQUES

Predictions for periods equal to or less than the solar rotation period. 27 days, are called fore-

casts. Disturbances in ploqress are described by warnings. A humher of centers throuqhout the worldissue warnings and short term forecasts of solar and ionospheric parameters 'Davies Iq7R . Twelve of

these are grouped into the International Ursiqram and Worl.1 Days Service lIMS' for the exchanoe of

data and cooperation in solar geophvsical observations. In the 1ISA the most important forecasting cen-

ters are US Air Force Global Weather Central im Tmaha and NtAA Space Environment Forecast renter in

Boulder. The USSR also issues short time forecasts (Avdvushin et a! 1979,. The forecasts normallv give

qualitative statements on the degree of disturbance expected, for eample 'moderate HF absorption" or

"general improvement of W4 propagation conditions". Forecasts for the degree of tEF phase disturbancpare often issued for PCA's; predictions for SID's have only recently been attempted experimentally'Swanson & Levine, private communication). Improvements in recent years in ionospheric forecasting are

due mainly to more efficient data acquisition and assessment. fxamples are the real time propagationassessment systems "Prophet" and the real time navigation monitor developed by the US Naval Ocean Systemrenter Rothmullor, 19781, 0Swanson & Levine, private communication'.

One interesting possibility for short term forecasting is to update a simple standard frequencvprediction proqram at intervals by means of some effective index of solar activitv )such as the 10.7 rm

solar radio noise flux) which can be monitored and distributed to the user. lffelman and Harnisrh'Naval Research Laboratory, private communication) have found that an update about every three hoursduring a maqnetic storm was sufficient to keep the error in the predicted 41F less than I Wt.

One of the important questions concerning warnings and short term forecasts is the timely distri-

bution of information to the user in a form that he can readily use. Even priority telex messages maytake 24 hrs to reach the user. A working qroup on D-reqion prediction Thrane et al 1979' has recom-

mended the development of telemetry for dissemination of disturbance informatinn to users. Fven one bitto indicate the presence or abs ence of a disturbance would be useful. Two methods were proposed asworth considering: a unique, non-interferinq modulation could he added to world wide Omeqa siqnals, or

to Hf-siqnals from WWV or elsewhere to indicate the presence of an event. The former has the advanv4age

that the Omeqa signal '10 kHt) is continuously available on a global basis, even d rinq total "f-

blackout.

6. MWTHODS FOR MINIMIZING HF-PROPAGATION PROBLEMS

From the above discussions it should be clear that propagation problems It "i cannot he elimi-nated, but may be alleviated by proper system desiqn and by the development of suitabl 'orecast ad

warning systems. We have pointed out the usefulness of frequency flexibility and path diversity for

avoiding problems durinq disturbances. One of the difficult problems farinq an Hf-operator is zr,ter-ference from other users of the HF band. Real time channel evaluation is a powerful tool hrth Foravoiding such interferPnceand for adapting to rapidly changing inospheric conditions.

It should be stressed that the ionospheric channel is not alwass available. Durino strnon natiraldisturbances such as PCA's or after nuclear explosions in the upper atmosphere, complete HF-blackout may

occur for long periods and Over wide areas. Wherever high reliability is renuirpd, back-up svstems toHF-communication are necessary. The difficulty is to desiqn back-up systems that have the ,implicitv,mobility and low costs of HF-systems. Transmission of VHf-siqnals via meteor trails is an interesting

possibility in this connection. Ionized trails from meteors occur in the heiqht ranqe 80-120 km andradio signals scattered from the trails may be observed over distances of 200 - 2000 km. the meteor

trails provide large bandwidth, short duration channels, which can be exploited using modern modulat iot,

techniques. Simple vaqi antennas suffice for this type of circuit.

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Solar-Terrestrial Prediction Proceedinqs 1, 104. US Dept of Commerce Boulder, rolo.

Relrose, 1.S. (1967). The "Berlin" Warming, Nature 214, 660.

Resprozvannaya, A.S., Shirochkov, A.V., Shchuka, T.I. (1979). On the approach to forecastinn polar

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Rradley, P.A. (1975). Long term Hf-propaqation Predictions for radio circuit planninq. Radio and

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CMIR (1978). Second CCIR computer-based interim method for estimatinq sky-wave field strenqth andtransmission loss at frequencies between 2 and 30 MHz. Supl to Report 2,2-2. Doc of XlVt ple-nary Ass ITU Geneva.

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Navies, K. (1969). Ionospheric Radio Waves. Alaidell PubI fo, Waltham Mass.

Davies, K. 1978). Ionospheric Prediction and fxtrapolation. In: Ed H Snirher, AGARP-CP 2jR, 1-1.

Georges, T.M. (1967). Ionospheric effects of atmospheric waves. FSSA Technical Pport VtP s'-ITgA S4,Boulder, Col.

Harz, T.R., Monthriand, I.F., Voqan, f.I. 1963). Canard J Phvs 41, 81.

Huinsucker, R.D., Rates, H.F. (1969). Survey of polar and auroral reqion effects on HF propagatin,.Radio Science 4, 347-36S.

Huns cker, R.t. '1975). Chatanika radar investigations of high latitude F-region iOn::atino sirirtuirpand dynamics. Radio Science 10, 277-288

Hunslrler, R.D. 'V479 . Morpholoqv and phenomenoloq of the high latitude {- and F-reolons. In: IR f Donnellv, Solar-terrestrial Prediction Pror 2, ,43 1(N Dept of Fommerce. Boul]er, olo.

lied. F., Iriksen, K.W., Landmark, R., Mhlum, 4.N., Thrane, F.%. 1967,. Niqh frequenr radiomunications with emphasis on polar problems, MSRfoqraph 1(4 techn:iision Maidenhead, nn!3nd.

I loud, 1.1 ., Hadon, G.W., luras, D.1 ., Teters, L.R. '1981). Estimatinq the pprrormanr of elnc-oo-msnioatino systems using the ionospheric transmission channel. Institute for Telpr'ommunicat i,-Sciences 'eport, Roulter, roln 90303 USA.

Manon, 2.H. '1981). Comment on "Morpholoqical features of the winter anomaly in ionospheriz' ah''rliv,

of radio waves at mid-latitudes" hv Teru Sato, I Geophvs Res R6, 1631.

Matesushita, S. 1'5). A studs of the mnrpholoq of ionospheric storms. 1 teophvs Res 64, %D"-21.

Meqill, I.P. 1960. Self-distortion of Radio Siqnals in the D-r.qion, Radio Science 69 1, %,,7.

Moller, H.. 1564d. Variable frequencv pulse transmission tests at obligie incidence ner distancesbetween 1000 and 21(1 km. West Deitscher Verlag npladen, Germany.

IOffermann, D., Rr.icielmann, H.G.K., Barnett, 3.J., Labitzke, K., Torkar, KM., Widdol, H.H. 187 . Ascale analvsis of the D-reqion winter anomaly, I Geophvs Res 8286-R6.

Rice, 0.W. 197h'. Hiqh resolution measurements of time dplav and angle of arrival over a 11 km NiPath. In: fg W Blackband, AG AR CP-175, 53-1.

Rothmiiller, 1.1. '19781. Real time propagation assessment. In: Ed H Soicher, ACARD CP-238 1, 3-1.

Rowe, 3.N., Ferraro, A.1., te, M.S., Mitra, A.P. (1969). Chanqes in electron density and collisionfrequency at Universitv Park, Pennsylvania during the stratospheric warminqs of 1967 68. J Atmterr Phvs 31, 1077.

Rdttqer, 1. (1978). Modelling the diurnal and seasonal variation of medium scale ionospheric disturban-ces. In: Ed H Soicher, AGARD CP-283 1, 19-1.

Sato, 1. (1980). Morphological features of the winter anomaly in ionospheric absorption of radio wavesat middle latitudes. 3 Geophys Res 85, 197.

Sato, T. (1981). Reply. J Geophys Res 86, 1636.

Schwentek, H. (1971). Regular and irregular behaviour of the winter anomaly in ionospheric absorption.3 Atm terr Phys 3, 1647-1650.

Skauq, R. (1981). Fxperiments with spread spectrum modulation on radio wave reflected from theionosphere. Arct fr CI"" und tkertragungstechnik 35, 151-155.

Smith, E.K. (1957). World wide occurrence of sporadic E NASCira 582, NIS Boulder, Colo 80303 USA.

Telleqeu, R.D.H. (1933). Interaction between radio waves, Nature 111, 840.

thrane, F.V. (1979). Reaults of transmission tests in Norway using high frequency radio waves reflectedfrom the ionosphere. Internal Report f-30, Norwegian Defence Research [at, N-2007 Kjeller,Norway.

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I lnCAPM Measuremnts

'Thrane and Pradiley lO~li

HF PROPAGATION MEASUREMENTS FOR REAL.-TIMECHANNEL EVALUATION (RTCE) SYSTeMS

by

Mario D. GrossiHarvard-Smithsonian Center for Astrophysics

Cambridge, Massachusetts02138U.S.A.

ABSTRACT

Recent adavances in microprocessor technology, in frequency-agile HF equipment and in the understand-ing of the propagation medium make it feasible and practical the adoption of adaptivity approaches in HFcommunications. Signal-to-Noise ratio, multipath spread and Doppler spread are the basic parameters towhich the link has to adapt itself. A necessary prerequisite for adaptivity is Real Time Channel Eval-anion (RTCE). Measurements of these parameters must be performed at several spot frequencies in the handof interest, in order to identify automatically the most suitable carriers for the transmission .f theinformation. RTCE is at present in the R&D phase, and the related activities emphasize the measurement ofsignal amplitude and noise levels (inclusive of interference) at several frequencies in specific HF pathsof interest, with a few instances of inclusion of multipath spread measurement. There is little doubt that.at the end of the R&D phase, RTCE and link adaptivitv will enter the practice of modernized HF coemnuni-cations.

A. INTRODUCTION, RATIONALE FOR RTCE MEASUREMENTS, AND PRINCIPLES OF SOUNDING/PROBING

I. General

HF propagation paths are time-siread and frequency-spread channels, and are characterized by severevariability in the time domain of all their properties, inclusive of path losses. In addition, ever whenpath conditions would he acceptable, the link might be severely interfered with by other transmitters.

Improvements over present-day link's performance in terms of circuit reliability, data rate and errorrate can be achieved through the use of adaptiv schemes capable of coping with the channel variability.

Real-time, oblique ionospheric sounding between the two terminals of the link, noise and interferencemeasurements at the receiving end, and channel probi-, simultaneously performed between the t', link'sterminals are the data gathering operations that provide the inputs on which to base the adaptive 'itrolof the link's performance parameters.

The master station of the link, where the sounding transmitter is located, could perf rr. a soundincgscan similar to the one made by an ionospheric oblique sounder of the normal practice, and c-uld alsogenerate the waveform for channel probing ( while operating as a complete termioal for to,,-wav digitalcommunications). During the pauses of the emissions, measurements of noise and interference ' uld be per-formed at both the master and the slave station of the link, for use by de, isIon-making mic rproess'rsand control units. At each terminal, the transmitting and the receiving facility could have separate unitcfor s-onding/probing and for communicating, or these functions could be performed by the same equipment indifferent modes of operation. In the latter case, the equipment at the two terminals Iould he identicaland the assignment of the master and of the slave roles would be dictated b 'perational requiremer:ts.

By processing the data obtained by sounding and probing. it would be possible to select automaticallvthe group of frequencies to be used for communicating. At each sounding cycle. information ab ut the fre-quenc selection and about the waveform to be employed is exohanged between terminals and is used ILallvto achieve adaptivity. During the next sounding scan, the group of frequencies that were selected forcommunicating could be excluded from the sounding frequency plan. Instead. tnformatin -o the changingstatus of the group of communicating frequencies could be obtained from measurements performed 'n the cod-ed waveform that is part of the communications bit stream ( Gupta and Grossi.l980 LI

1 ; 1-81 2].

The properties of the path that must be monitored In real time are

I. Noise and interference spectral density2. (Signal + Noise) level3. Multipath spread4. Doppler spread.

It would be useful to know accurately the time variability and related statistics, of these properties,Unfortunately, this information is available only for particular cases, and a reliable experimental investi-gation on the properties above is thus far an unfulfilled requirement. In general, we can say that theseionospheric channels exhibit time fadings that are important in determining the design of the sgnal and.in addition, show long-term variations due to large-scale fluctuations of the medium. Such slow effectshave a time constant significantly greater than 5 to 10 minutes, an interval of time that appears appropri-ate as the basic sounding/probing peridiocity. Adaptive approaches to the communication problem are requir-ed to circumvent this long-term variability in propagation conditions.

In this lecture, we will make the usual distinction between path sounding and channel probing, with theformer devoted to the measurement of path losses and of noise and interference levels, and with the latter

devoted to the measurement of such parameters as multipath spread and Doppler spread. The following cri-

teria were adopted:

1. The link is assumed reciprocal, except for the noise and the interference levelsat each terminal. Therefore, the decision on the frequencies to be used ( this

decision is based on the results of the sounding operation) is based on the measure

ment of interference and noise both at the master and at the slave station, and on

the one-way measurement of the path losses between the two;

2. Processing of the multipath spread and of the Doppler spread data ( provided bc the

channel probing operation) is performed at the slave station, and the results are

transmitted back to the master station, for use in the final selection of the fte-

quencies to he used in communicating;

3. Channel probing is to be undertaken oniy at the best frequencies put in evidence by

the path sounding, in order to shorten the overall operation sounding/probing.

It was assumed by Gupta and Grossi ( 1980 [i] ; 1981 [21 ) that a very large number of spot frequeocieswas available to the adaptive link: 1125 or 3375 carriers, respectively for a mid-latitude and for a crans-

auroral path, in the Land 3 to 30 MHz. These authors advocated a tightly integrated sounding/probing/cornuni

cations scheme, in which a set of frequencies was simultaneously transmitted to achieve waveform diversity.

The power density (Watt/Hz) at each frequency was low enough to be received below noise by standard HF re-

ceivers, as long they were located outside a circle with about 100 Km radius, centered at the link's trans-

mitting terminal. Only those receivers that were coherently processing the waveform containing the infor-

mation to be exchanged between the two terminals were able to detect the waveform above noise. The sound-

ing scan proposed by these authors was lasting 100 to 160 seconds, and was repeated every 300 to 480 sec nds.

More recently, Aarons and Grossi (1982, [31 ) have proposed an approach that reduces substantially the

number of spot frequencies at which the sounding is performed. They pointed out that achieving corvpletc

adaptivity to the path is impractical: too many spot frequencies arc needed. Altiough. in principle, a

frequency-spread waveform is the way to go, there are practical limits to this spread. If adaptivity, the.

cannot be extended beyond certain constraints, we cannot dispose ot the continuing need f -r ,nospheri,forecasting on the path. and of the need of warnings about magnetic stores and solar prot u, activitv. A

hybrid approach, where the traditional forecast ig and warning funct os are kept intact, and Ahere thesystem is made partially adaptive (within practically acceptable limits), represents an advisable appr,,ach

toward improvement and modernization of HF technology and systems.

Aarons and Grossi advocated that forecasting shovld continue to coexint with adaptn.itv.i- ,rdr toprovide a first-cut identification of the frequency windows that are available for use in the channel, a,

a function of geographic and geomagnetic coordinates, time of the day. sunspot number. etc- F,reLasti!vg

shuld a(tually he extended in scope. to inclode the predictio of the time-spread a-d ,f tie freque -

spread of the path. Concerning the ionospheric warning function, we should expect that the ue of s, larmagneti sensors will als be continued These sensors make it possible to have ar-lng lead times thatrange frs a lew minutes to several hi-urs, s-fficient therefore to ad ust system operation to the t,,rth

cioming i nditilns of the path. Early knowledge of PCA events, f magnetic storms and ,f similar phelnc'ta.will be a prerequisite tor -the -ffective performance of an adaptive system. Choice a,d am A ,sc -Iathodiversity, amount of data rate, extent of use of error-correction sciemes. ec, , are all fusition that 'a

be optimized by the simultaneous use ,f forecast/warning and partial adaptivits.

As in any adaptive approach that involves real tim, data gathering to ad;ust the parameters ,t a-, eic.Lr

c,.netic system to the propagation medium, the preferable way is to adapt , first of all. the svsten to thcbest a-priori model of the medium, in our case, t,' the midel ,of the HF ionospheric path. Generally, this

model is a software subroutine stored in the memory of the microprocessor that is used in the logic unitsof the system. This model is periodically modified and ad isoted to reflect the instruct -os of the fore-

a-;t ing and warning operat ions I functions. It is then updated and brought in cI o-e agreement w; th the a tus I

path conditions by means of real time observations per',,rmed be the communicatlons li--k itself rI appracof this kind has been already succesfull impleme.ted in correcting for ion-spheric-induced errors in high

performance radars (Katz et al., 1978 [4 ). Figure l( taken from Aarons and Grossi. 1982 [1J ) gives the

block diagram of principle of this HF communications approach. The combinati.o of mean-model plus real-tme

updating should be taken in serious consideration, when designing mnit-genierat i-n HF cssiyatins Ii-ks

In order to help visualizing real-time sounding and probing, we illustrate in the following Se ,ti's

2 and 3 ) the scheme that was conceived by Gupta and Gr.isui ( 1980 [iJ ; and 1981 [23 ).

2. Path Sounding

Path sounding has the siope of measuring path losses at an adequate numbec of spot freq'jot-iies i- thehand of interest ( 3 MHz to 30 MHz) and of measuring at the same time noise anid ivterferace lec, Is. at thle

same frequencies and at both ends of the link

Table I gives the parameters of the 'ounding scan proposed by Gupta and ;rLsSi (198o1 U ) The mast,r

station radiates sequentially 1125 to 3750 carriers to cover the 3 to 30 MHz band. in a t:me i-iterval 100to 160 seconds long ( 88 to 47 milliseconds per iarrier). Of the two values gtiveT above . oaib s -- ding

parameter, the first applies to a mid-latitude path, the second to a transaur,ral path. The sian is repeat-

ed every 5 to 8 minutes.

Once that a set of frequencies has been chosen for coeeuntating, it is automatically ecnluded from. next

sounding cycle. However, information on tho channel status for each one of the frequent ics excluded fr-rnsounding and probing is still updated once every S to 8 minutes by measurements performed on the commuit-cations waveform. Frequency switching isprc.eded by a "tone" of notification and takes plate even while

communications go on, for the case in which the shanoiel deteriorates and another set of frequencies is found

r oiitahl t, arry -it I'lmunucat o-s. !.hl, ',I 'T k :agrar : F:e:.r- - )cr ta:s a .a,. a0ap;tand liustrat s tie vart,'us IfI-ti rs i tt, t- tr-..a-. >e -I- -o -, r ac .1 r - pr . s a,:-

this .se IrL th- ae tn t., the la- tai , AkI1-g-- t a fr th,- -ac t t 1,tLta t a t., IIt' IatL i ,is are i,--ar e laoges btg ' tIe t 'tat

TABLE I - Soundin Scan Parareters

,it- at. t:c Pat rt:arr ra I patsl

Band I r -d : MB; t' ' C N iiz ;1 14Number , rpot trequenices 1.2$ 3 5

S'parat t,, b-ts-e: t-'

ad a L pt fr-quencies 24 IlZ 8 rlz

Sounding scan time 100 seconds 10 secondsRate of sounding scan

repetition ,ne every 300 one every ,80

seconds secondsDwelling time per spot

frequency 88 milliseconds 47 milliseconds

Nominal bandidth ,fsounding receiver 24 0i~z 8 K1I.

Width of sounding pulse 41.5 microseconds 125 microseconds

Pulse repetition frequeny 100 pps 100 ppsPulses per dwelling time 8 pulses L pulsesNoise and interference

measurement 's integrationtime, for each spot fre-

quency 53 milliseconds 47 millisecondsOverall noise and inter-

ference measurement time 60 seconds l60 seconds

(5) This value is chosen because 8 Klz is the bandwidth of the signal waveformselected for the transauroral link. The path coherent bandwidth is oilyb66 He.

(from Gupta and irossi, 1980,[l) )

The sequence of steps through which sounding and probing are performed is as follows:

For the mldlatitude link

Step I - 100 seconds devoted to sounding operation.

Step 2 - ti seconds devoted to measurement of noise

and interference at both terminals of thelink.

Step 3 - 20 seconds devoted to computations, takinginto account the need of accumulating at a

single terminal (the slave station) the ir

formation pertaining noise and interference

at both terminals. During this step, the microprocessor at the slave station selects

the frequencies and designates them to themaster station.

Step 4 - lO0 seconds devoted to channel probing, to

be performed only at the frequencies designat

ed by step 3.

Step 5 - 20 seconds devoted to computations, acknow-ledgement and information exchange betweenthe two terminals, in order to perform the

final selection of frequencies to be used incomunications,by taking into account thedata on multipath spread and Doppler spread.

Step 6 - The two terminals are now ready to initiate

communications. The frequencies finally adoptad for comiunications are excluded from next

sounding/probing cycle (one every 300 seconds),although they continue to be monitored by me!surements on the modulation waveform.

For the transauroral link

Step 1 - 160 seconds

Step 2 - 160 seconds

Step 3 - 20 seconds

Step 4 - 120 seconds

1 4

Step 5 - 20 secondsStep 6 - The two terminals are now ready to initiate

communications. The sounding/probing cycleis repeated every 8 minutes (480 seconds).

Comsunications are therefore inhibited only in the first 300 ( or 480) seconds f link operation. Afterthis initial adaptive adjustments of the link's terminals, any readjustment is performed without requiring

a discontinuation of communications.

3. Channel Probing

The importance of time-dispersive and frequency-dispersive effects in HF propagation has been amplv

treated in the literature. These effec--are-i ermining factors in the conceptual design of an adaptivesystem. Channel probing is aimed at gathering information on these effects, after the path sounding hasdetermined path losses and noise ( plus interference) levels at the available spectral lines, and has i-dentified the frequencies promising enough to be worthy of the channel probing effort. All these functionsare slowly varsing functions, so that one sample every 5 to 8 minutes is adequate. The smenureent f multipath spread and Doppler spread can be achieved with a variety of rethods, either based on the direct measure

ment of these two quantities or on indirect measurements such as the ones based on the fact that, at a given

frequency, the reciprocal of the Doppler spread gives the fading period of the arriving e.m. wave, or that

tie reciprocal of the multipath spread, at a given instant of time, gives the frequency interval cithin

which carriers fade coherently. Because the amount of time required to process the information n the dis-persive properties of each channel is not trivial, these measurements should be performed only for thosefrequencies for which path sounding has indicated acceptable path losses and affordable noise and inter-

ference levels. Therefore channel probing has to follow, in time, the sounding operation.

Ideally, channel probing should provide a reliable estimate of all the parameters of the path that

are indicated in Figure 3, 4. and 5. These are the quantities B d. Bm and the function S( , ), called the path's scattering function. In actual practice, it is sufficient to simplify the scattering functin

t, a gr up 'f N gaussoids, with B 1O, Bd =0, and to reduce therefore the function to the one shown in r.ss-secti n in Figure 6 and 7. An intuitive picture of the scattering function can be obtained as follows. Sup-pse that the path is such that a pulse of infinitesimal length is transmitted unaffected and that a

sp., tral line of great purity also, is not broadened. We can say in this case that the scattering tunction

t the path is

sP., )e i t ii" S

In .ther words, the scattering function is the product of two delta functions. This is a highly idealized

case. Is real propagation, an infinitesimally shrr pulse, and a spectral line of infinitesimal width, are

actuallv broadened, respectively in the time and in the frequency domain. This causes the scattering func-

tin t, have a finite width both along the frequency axis and the time axis. Figure 8, taken from Green (S],IsP), is useful in visualizing the relationship between scattering function and other well known channel

functions, such as impulse response, etc.

Cl ,ong hack to Figures , and 7, the analytical expression for the scattering function becomes:

S(",)= Pi (21 B L ) Iexp -i (, - +) (_L)2

iL i

In this formula, the parameter N represents the number of paths in the structure, :i and Li are the meandelay and the multipath spread, B is the Doppler spread of the path, and P. represents the relative strengthof tile ith path. Further simplifications can be achieved by representing te scattering function as a singlegaussoid, whose amplitude is a function of the path losses and whose width Ltnt and Btot (Figure 5) are re-pectively the total time spread and the total Doppler spread.

The measurement of the properties of a communication channel is particularly important in digital cormeunications, because high-speed data transmission critically depends upon them. Kailath( 1959, j ) pointedout that the problem of the measurement of the system functions in random, time-variant, channels might beunsolvable. This author introduced a parameter called the "spread factor" as the measurability criterion.If the product of the maximum Doppler spread and of the maximum multipath spread is larger than unity, andif no other information is available on the channel, the channel parameters cannot be measured accurately.Fortunately, for ionospheric HF paths, the spread factor is less than unity, so that standjrd measurementtechniques, as the ones described here below, are applicable. Bello and Esp sito ( 1970,L7J have analyz-ed these measurement techniques for random, time-variant, dispersive channels, and they list them in threelevels of increasing complexity:

I. Measurement of mult-path spread and Doppler spread;

of Doppler shift and spectral skewness;

2. Measurement of second-order channel functions;

3. Maesurement of instantaneous channel functions.

For the parameters in item 1 above, measurement techniques used are based upon differentiation, levelcrossing and correlation. For item 2 above, the techniques used are correlation techniques, esultitone approach,

pulse pair method and chirp technique. For the measurement of the parameter, in item 3, the methods used arethe cross correlation, the multitone approach and the pulse pair technique.

S

G upta and Grssi (198,] ) give an account of tie methods usable in probing the channel and i!lu trate pssible hardware implementations. They review the measurement of Doppler spectrum pararieters, thesimultaneous measurement of Doppler spread and multipath spread, the determination of the Lnstantane' iimpulse response, as well as the measurement of time-variant channel functions and ,f channel c rrlatz.::functions. In this lecture, we concentrate on the methods for measuring the nultipath spread and th :.'yplerspread, that are the two channel parameters characterized by the highest priority.

B. TECHNIQIES FORP RPEAL-Tli. (iHANN. EALUATION ( RTCEI

1. Introductory remarks

Measurement of Signal intensity and of noise levels (inclusive of interference), together -ith thedetermination of multipath spread and of Doppler spread are the basic obtectives of RTCE funccios. rhesequantities are fundamental prerequisites to achieve link's adaptivity. Cf the three parameters, teciniquesfor the measurement of signal and noise are well known and already part of HF communications practice. .ewill briefly review them in the summary at the end of this Section. Our attention will focus or the voredifficult task, and on tile less known related approaches, concerning the measurement of multipath spreadano boppler spread. ide have already indicated, earlier in this lecture, that instead of measuring the c o-plei scattering function, it is sufficienr, and obviouslv simpler . o measuse the delay power spe.trut'( - and the Doppler pwer density spectrum P B ) ( Hell, 1963 LS; [9b5 L9J ).

Multipath spread neasurement

A signal wavef rr that appears an hvious choice for estimating the Delay Power Spectrum ( s i asi rt pulse f time duration . narrow in width when compared with the characteristic variatio: s in .t .C ider thr signal

,(t) pt)

0. ItI- /2

pit)1 It .

' 12

c individualpath width ( mode width)

Ani estir.te cat, be obtained by square-law detection of the observed process, and by subtracting fronm itthet noise bias. Thus, for the response to one of the pulses in the train, we have :

-hr Q- n (tr7 jn I) p (t - d r n it)

where tr

r(t) yA Wit) + n it), received signal intensity

It ) rms noise level

noise variance

A average power level of received carrier

g C ) time-invariant response of the channel to an

+O0 impulse seconds earlier

w( t ) .i(t,r )z ( t - ) dy , channel output

From the equation for Q it) written above, we can determine the range of delay values wherein g(t,:as a function of ,is negligibly small. Thus, if

g ( t, ) - 0 , for c win and for i -

then, the wanted delay spread is given by ,, winmax 'min•

Q (t) will be a filtered version of the true function, if sufficient averaging is carried out. The measure-ment resolution is determined by the signal properties, so that the pulse width mist be narrower than the modewidths of Q ( ), to give an adequate estimate. However, even in the beat possible conditions, the noisecontribution to the estimate of the variance is significant. This conclusion applies directly to the measure-ment of the peaks of Q ('4), and some allowance must be made for the accurate measurement of the low-leveldetails of Q ( ). Therefore, the single pulse approach appears to be unadvisable, because of Its require-ment of high Signal-to-Noise ratios.

An alternative estimation scheme can be utilized, if there is the possibility of carrying out coherentprocessing at the receiving terminal. Let e(t) be a pseudo-random sequence of period T, which is used to mo-dulate the carrier ( bit length equal to. ). When the sequence is periodic, it can be assumed to have the

following property

T

( t) z (t- : dt (-

with j:=0 , =0

U(s) is:(0) ,[ .

where nN = sequence length T / = 2 - 1

and where :(0) is the energy in one period. When we are, then, interested in transmitting only a singleperiod before switching to a different channel, we have

0 , 0s t T

7° (t) =oz (t) , otherwise.

The autocorrelation for this aperiodic z(t) sequence has been shown to have properties similar to th.seof a periodic sequence, i.e. : -

( =7 ) zo(t) zo (t- 3 dto: 0

0(0) 0

, 0) ,,

V-

and the estimate is of the form

+ 12

Q (7) = r(t) z ( t d - bo Io

where b is the bias term. The integra in this equation can be mechanized by multiplying the originalsequence ( which can he generated using phase-reversal keying, thus implying that z(t) is real) against thein-phase and quadratere components of the received waveform. This is followed by square-law ( or possibly,linear) detection and by an integrate-and-dump procedure, using a low pass filter with time constant greaterthan T. To implement the scheme for a set of values, requires parallel processirg and possibly the use ofa tapped delay line. The number of taps depends on the product of the signal bandwidth w the delay range(, ) to be observed. Figures 9 through 13 indicate a possible mechanization approach for the transmitterand for the receiver. Not included in the block diagrams are the logic units required to switch through theset of frequencies at which the measurements mst be carried out.

3. Doppler spread measurement

The Doppler spread of the channel is best observed using a CW source. However, the fading rate in 1iFionospheric channels is relatively small ( B ' I Hz) so that an efficient measurement of the Dopplerspread requires the use of a sequential sampli8l approach, in cases, such as ours, that a group of channelsmust be monitored. Individual channels have to be probed periodically at intervals To ( TO , 1 /Btot) to

give useful estimates, By probing at a faster rate than required ( To 1/Bt,), Information is obtained

which is redundant in terms of the Delay Power Spectrum estimate, but which may still provide useful datafor Doppler spectrum estimation.

Let's consider the sequence of outputs [f ( nT0 )J obtained when the equation

+' x o 2 -- )r(t) z t dt b

is implemented. For a particular T , we have

Af ( nT ) - Q ( T (estimate at nTo).o nT o

Then, it can be shown that, if the sidelobe interference is neglected, we have

f (nT) - g ( nT, )

eo

Thus, any spectral information obtained from this sequence of outputs cill relate to the shape of thescattering function for this particular delayt . If the Signal/Noise data are used, the complete spectrnmis involved, and from the previous equation, we have:

f (oT ) A w(nT ) A ( n , d I

Because of the inherently higher Signal-to-Noise ratio, it appears that the latter sequence offers the test

alternative for spectrum analysis. In addition, the total scan time T required to probe all .halnels once.

is significantly less than for the wideband coded sequence, thus proAding higher sampling rate and lower

danger of aliasing effects.

Before discussing spectral measurement schemes usable in our case, it should he noted that the phase in-stability of the oscillators used at each terminal, if not kept under acceptable levels, imposes the use of

an incoherent Doppler measurement approach. If phase coherence can be assumed for the link. then the in-phase and quadrature components generated at each T seconds could be used to obtain the spectral properties

directly, o

Concerning then the estimate of the Envelope Correlation Function. we note that for a complex Gaussian

process, the envelope correlation function is closely related to the process correlation function. If f(t)

is complex Gaussian, and

f(t) C ) - Rf ( t - u )

then

f (t) f (0) + f t - u

Thus, if the average power is already known, an estimate ofI R f2 follows from an estimate of the correla-

tion function for f (0)2. If we let Rf 1 2 (t -u ) to be the estimate of f( t f ( 2, then we

have

R f t u R f (0).' (tu 2 jZ(t-u)

Note that , without imposing further constraints, the estimate may he negative, particularly for insufficientaveraging.

Concerning the implementation of this scheme, the sequence f (nTo) is first divided into blocks, the

length of which determines the resolution of the spectral estimate. For example, a Doppler resolution of

0.2 Hz requirls 5 seconds of data. Each block of data, 5 seconds long, is used to provide a single estimateof R (.)[ , or its Fourier transform. Thus, in this example, 12 individual estimates are performed andaveraged in 60 seconds. The sequence of samples in each block can he used to find either the correlation

function or the spectrum, directly. If a spectral analysis of the samples is performed, the form of toeequation above suggests that the resulting spectrum will contain an impulsive term at the origin, ad generally have a width of about twice the width of the spectrum of f(t). Note that the sampling rate l/T

°

must be consistent with the maximum Doppler spread expected. in order to avoid aliasing effects.

Several techniques for real-time estimation of spectrum parameters are illustrated by Bello ( 1965.[93).

These techniques make it possible to perform the measurement of the center frequency and of the rms band-width of a narrow-band process. The center frequency is the centroid of the power spectrum of the process,

whle the flma bandwidth is twice the radius of the power spectrum. The same technique may he applied to

hf (nT ) so that the width and the location of the spectr-um may be determined. We briefly summarizehere under the measurement technique and the effect of additive noise for a complex low-pass process g (t).The results will then be specialized to the real envelope process. Let

g(t) x (t) + I y (t)

< dxdt

dt

with the triangular brackets denoting time averages. From the analytical conclusions of Bello 190, [9lwe can readily see that the centrold of the power spectrum of g (t) is given by

1 <0 - yi> - S(

2 2

where S ( o ) is the spectrum of g~t). Tlb s badw d ,h is gIvan by : ( 2i ()

<2

+y2

> f . ) d.

+w

The influence of noise is readily taken into account by noting that the complex additive noise N(t) isa complex Gaussian process like g(t), so that the measurement will produce the centroid and the rs band-width of the power spectrum of g(t) + N (t), namely:

C ft IS + P1 ] _dvIs(- + PN d.

f[ + d.

j': i - C.)2 f -. ) + P~i )] d.

Bs i. )+ P(.. )_] d,-

where P.,i . ) is the power spectrum of N (t). The in-phase and quadrature components ( x , y ) can bedetermiied by multiplying the received carrier by both a local carrier and a 90

° shifted local carrier at

the same frequency, and then extracting the low-frequency components . Strictly speaking, D is independentof mean Doppler shift, and thus precise knowledge of the received carrier frequency is not necessary. How-ever, as the local carrier frequency departs from the received carrier frequency, the extracted x(t) andy (t) increase in bandwidth, thus requiring filters with larger bandwidth, that let more noise pass through.Thus, from the point of view of maximizing the Signal-to-Noise ratio, it is desirable to keep the local,arrier fre,,uency as near as possible to the received signal frequency.

We consider now a simpler technique for the measurement of Doppler spread. It uses only t'ie encoelope

,r, more generally, any well-behaved non-linear function of the envelope of the received carrier, For thistechnique to be strictly correct, it is necessary to assume that the transmission of a carrier results inthe reception of a narrow-band Gaussian process. However, a slight departure from this condition would notaffect significantly the measured parameter. It was demonstrated by Bello ( 19b, L9] ), that, if e(t) issome non-linear function of the envelope x

2 + y

2 of the received carrier, the rms Doppler spread is given

by

D < Ce (t 2>

where , is a constant dependent upon the properties of the non-linean deViLe used. Thus, if we describethis non-linear device by the function k (.), we have

e (t) k x + y 2

and it is shown by Bello (195, [9] ) that

S Jrer [kr)/dr]2 dr

00-rI e (r) dr

In the case of a linear envelope detector, = 1/1 72' and for a square-law detector, a I. The formationof the derivatives of the envelope from sampled data requires particular care ( Bello, 19b,[] ).

4. Summary and recapitulation of channel evaluation techniques

a) Measurement of Signal and Noise

This can be best be achieved by using an "off-on" keyed signal, with the noise measurement preceding the signal measurement at any given frequency. "hoosing for the noise measurement integration time thevalues indicated in Table I, the estimation of. can be performed with adequate accuracy. The signal levelalso must he measured by averaging a sequence c? observations. Table I gives two examples of pulse widths.pulse repetition frequencies, and overall rime required for both Signal and noise determination. The measurement accuracy for signal level estimation is limited by the channel fluctuations, i.e.

AVar C A ) - / N

A2 eq

where Ne is the number of independent observations available in one sounding scan tLmds( let's take the

case of the midlatitude path in Table I)repertion period, which is 300 seconds. Because the fading rateis 1/Bto1 * we have N - 300 B , If B - I Hz, we have that N - 300. The noise level estimate

hsartoeq tot tot eqh a s a r a t i o a & ) 10 -Vart~&'n) 1 ._..!_ 7.86 l0-

4

TV

again , by taking the numbers in the colurm of Table I devoted to mid-latitude path ( 53 millitec x 24 lOrz ).

b) Measurement of Doppler spectrum characteristics

The accuracy achievable in these measurements strictly depends on the dwelling time on each freqjencvat which channel probing is performed. If we want, for eaxmple, a Doppler spectrum resolution of 0.33 Hz,we require an observing time, per frequency , of 3 seconds. In the example that we gave immediately afterTable I, in page 9-3, we chose 100 seconds as the time devoted to channel probing ( Step 4). By assumingthat Doppler measurements are performed in a non-interference basis with the other measurements, only 33carriers can be measured in the allotted time interval. We can see therefore that determination of Dopplerspread is very demanding in terms of length of observations.

c) Measurement of delay power spectrum

Two types of signals can be considered:

I. Single pulse

0 otherwise

p~t)

2 . Coded sequence ( phase reversal keying)N

Zo(t) = k ak p( t - k )k=1

wherea = +1kN = 2

m -

T = N = total duration

The coded sequence gives the same performance as a singlepulse for equal energy; i.e., if Pl.. p2 T neglectingdegradation due to sidelobe structure of sequence autocorre-lation function).

Concerniag the measurement of Q ( .- ) in absence of noise, the basic limitation in accuracy achiev-able is the number of independent channel's "snapshots" ( impulse responses) that can be obtained in onescanning cycle :

A 1standard dev. ( Q =

mean rN eq

In presence of additive noise, performance depends upon the shape of the true Q ( ) being measured. Let'sconsider an idealized function consisting of M equal rectangular modes:

I

0 ; during mode ( L o is the duration of each mode)

0 ; elsewhere

Then, at the mode centers, Q ( ) can be estimated with the formula:

Astandard dev. + n

mean (E ( ) ) I Q ( .)

where

noise variance in the receiver bandwidth

E = equivalent pulse energy

A single pulse will not give adequate performance. When a sequence of length 215_ I is used, estimation ofQ ( ') will be limited by channel fluctuations rather than noise. Because of the large number of frequenciesbeing probed, the overall (noise-limited) performance is degraded.

C. CONCLUSIONS

Adaptive HF approaches can be kept limited in scope and made to respond only to the variations of a

selected channel paramter, such as Signal-to-Noise ratio. At the other extrer . they can be designed asall encompassing and capable to respond to all relevant channel functions, such as SNP., multipath spread,

Doppler spread, etc. We have seen in this lecture pertinent examples. The RTCE data gathering must parallelin scope the adaptivity scheme that it is meant to serve. For instance, if data rate is ad usted .rlv toSNR, the RTCE must be kept very simple and must be reduced to the sole measurement of the signal intinsit%and to the level of the noise ( inclusive of interference).

In this lecture we have given examples of adaptivity schemes.and of related RICE approaches, thattended toward the complicated side (see, for instance, the scheme depicted in Figure 2). This was donebecause learning of a complex solution makes it easier to visualize the simpler ones. There is littlequestion, in fact, that the simpler solutions will enter the HF communications practice tirst. and thatseveral years will pass before we see in operation a system such as the one depicted in Figure 2. Eventhe RAD activity presently underway on adaptivity schemes and related RTCE techniques, is almost exclusively limited to the investigation of link's adaptivity to SNR. However, there is little question thatthe demand for high data rates, and the quest for better HF link's performance ( to bring this chazinelup to the quality of competitive approaches)will provide enough motivation to implement in practice presentday designs of adaptive links, that will necessarily include RTCE features. All these improvements sillenter the practice gradually, with adaptivity to multipath spread and Doppler spread coming last. When theywill he in place, the era of truly modernized 4F comnunications will have come.

1. BIBLIOGRAPHIC REFERENCES

l1 Gupta A.K. and 5.D.Grossi (1980), Adaptive HF propagation path utilization, AFGL-TR-79-O2o. FinalReport on Contract F 19628-79-C-0137. SAO, Cambridge, MA, June.

G2] upta A.K. and MD.Crossi (1981), Adaptive utilization of HP paths : A way to cope with ionosphericlimitations affecting mid-latitude and transauroral short-wave links. Proc. 1981 LES Symposium onthe effects of the ionosphere on radio-wave systems, NRL/ONR/AFGL. 14-i April, Washington, D.C.

[3) Aarons J. and M.D.Grossi (1982), HF propagation factors affecting the design and the operatin -freal-time, channel evaluation, adaptive systems, NATO-AGARD 30th Symposium of the E.M. Wave Propagation panel, Copenhagen, Denmark, ?:ay 24-28.

Katz A.H., M.D.Grossi, R.S.Alten, D.E.Donatelli (1978), Adaptive correction of the effect of theionosphere on range determination by terrestrial radars, IES 1978, NRL/ONR. Arlington, VA, laouarv24-26.

[15 Green PE., Jr. (1968), Radar Measurements, in Radar Astronomy , Edited by .I.V. Evans and T.Ragfors,Publisher: McGraw Hill Book Co.. New York, N.Y.

LbJ Kailath T.J1959), Sampling models for linear, time-variant filters, MIT-RLE Report N. 352. Cambridge.Massachusetts.

L7] Bello P.A. and R. Esposito (1970), Measurement techniques for time-varying dispersive channels.Alta Frequenz (English issue), Vol, UXXIX, No. I. pp. 980-996, November.

[8) Bello P.A. (1963), Characterization of randomly time variant channels, IEEE Trans. Comm. Svstems,pp. 360-393, December.

B9] Rello P.A. (1965), Some techniques for the instantaneous real-time measurement of multipath andDoppler spread, IEEE Trans. Comm. Techniques, pp. 285-292, September.

40

Real- tin.P. th S uIdi

LTar

t ricat

Iradjti-iai

IFAd istr-t'r a :id s

IC rsr It rid Xodel Ad i te

Ad p

( taken Iton ( upt iidm ( ,roi . I )KII I

fI g I \ltiii1 scatterting lun~tiori S (j.

0CC)

LL2

Fjg.4 Multiiodal delay power spectrumi Q it)

Sly')

tot

Fig.5 Single modc D~oppler power spectrum S (P)

--2,ll -v -- l 1

-4-

t -2 1 lI0 10 20O30 40 50 60 70O 80 901I00 110 '20 130 140 50

DELAY /s¢

I4

0 - -0

IF F

I5#s 5 DELAY/ t 15.se

11 f 1tl 1 I 0/ $ ,It I 0': III IO

} ." t< +',+'++t<rIH lh++ I'}I~ L = 5 x 1

, l rt) il l~)) tth ++

111 :I TIII' z

1 -4

NTARE SCATTERING FUNCION

I..O IPAWCTRUM POWER Inpt. S( PONSE

j F O U Eft T R A N S FO R M F O U R IE R T R A RI O R M 'O R I C I T R A N S FO R M

AT

AIIA4 ~ oI/L At

CORRELATION FUNCTION 04ORREP.LATION FUN.CTION

A?

TwWO@lCIC CORRELATION FUNCTION

Fi-gM Staiiary of the interrClaitonsilps ot the target (chlanl I scdjttcnfg fuinctionaril other descri ptive tiund ons I f ikeni tro in ( ;reen. 1 148

FSE UDO

C ODE GEN.

AvA..ANCHE PF - AL.AD IODE H~AS! TH F-E R PESOURCE 0 -101

__POW1 I,5 0...

Fig,) Bllock diagram ol transiflittVr

I N-PHASE 1-HS

AND A..--GUAD ''7 -

j ~STALO AFc- DEO

SU. SYSTEM -IN-PHASE -

REFERENCE

REFERENCE

D1ELAY ERROR _ F OALNETwORx 'ROM DE9MODS

PEC CODEROR DSPt AyAND DELAY

P.1 REF ~EYAOR4

PSEUDO RANDOMRE ODE R ATCLR SPE r,'E

Fig. 10 Bllock diagram of'receiver

12-16

FROM IF ARW IIA

SANG ~ S ,ITR M,NAORn STANDARD

AND/OR REA

P COM

D AD ELAtPWE

PROIF SHIF

REGISTRER

Fig. I 1I Block diagram Auo aic Fndequedcyonultrolrs

ERROR/O SRENA

PR M DLY i TIGeRSQUNE T SAESI E' TIMEf PROEISER

0R SESECRE E EN E TO

S

DEoODELETORR

AM. AQVANCE.REWA

BUTFE LOFFIC

ADVANCEAS RETARCOMMANDO COFAN

F ig. I Block diagram ol R ieeo and heidtrgstr

ADAPTIVE SYSTEMS IN OPERATIONby

L.E.PetriePetrie Telecommunications

22 Barran StreetNepean, Ontario K2J IG4

CANADA

ABSTRACT

The development and evolution of channel evaluation t-,hn . is i es ribe!.A recently developed fully automatic IF radio 'elephone syste- is liscussed whic:;automatically selects the suitable channel and also provides a telep:hone int-r-connect. Also described is a HF message terminal which automatically r-quests,repeats and confirms message status fcr sender anO receiver.

1. INTRODUCTION

In the early 1960's, real time channel evaluation (RTCE) systems were firstused to improve the performance 3f operational HF radio systems (Jull et al, 1962;Stevens, 1968). These systems were rather rudimentary as far as todays technologyis concerned. The channel evaluation was done by equipment sepirate and indepen-dent of the communication transmitter and receiver. The RTCE equipment switched toeach assigned frequency channel, measured the signal-to-noise or interferenceratio and recorded the usuable channels on a paper chart recorder. The radio oper-ator selected the channel for communications by examining a history of the perfor-mance of all channels over a specified period of timle. Since the 1960's, the RTCFsystems have become more sophisticated and an integral part of the communicationtransmitter receiver equipment. Micrprocessors are now used to control the equip-ment operation and measure the parameters necessary for an adaptive system tooperate effectively. With the microprocessor, additional features can be addcl,such as a calling system in which a base station can call a specific mobile ter-minal or a number of mobile terminals automatically. Various types of RTCE systemswith different degrees of complexity are operational today. A recently developedHF radiotelephone system with automatic channel evaluation features is describedin Section 2 and an HF message terminal that can be added to any type of systemis described in Section 3.

2. RACE

A system named RACE (Radio Telephone with Automatic Channel Evaluation) wasdeveloped to improve the quality of telephone services provided by HF radio toremote areas (Chow and McLarnon 1982). This system not only evaluates the perform-ance of each channel but also eliminates the requirement for an telephone operator.The RACE system consists of one Master and a number of Remote terminals. Each ofthese terminals consist of the following three subsystems as shown in Fiq. 2.

a) Contoller Interface Unit (CIU):The controller Interface is essentially a microprocessor which prov.ides

- an interface to the telephone system;- transmission and reception of dialled digits and supervisory

data over the HF network;- channel evaluation and selection;- control of the HF transmitter receiver system.

b) HF Transmitter Receiver System:This system consists of a conventional single side band transceiver withcapability of a channel being selected remotely by means of a digitalsignal from the CIU. Broadband antennas are used to facilitate rapidswitching of the channels.

c) Syncompex Unit:This unit is a speech processor using digital techniques (Chow andMcLarnon 1981) which improves the performance of the channel whenthe signal-to-noise or interference is low and provides a marginalservice. Incorpoated into this unit are 75 bps dual diversity FSKmodems which also provide the data link for establishing a call toa subscriber.

In the RACE system the channel evaluation is done by transmitting dataon available channels during the idle periods when the system is not occupied byradio telephone calls. Each Master station transmits a burst of FSX data, calledan idle message, on each channel in turn, and all Remote stations synchronizethemselves to the Master station and evaluate the received data by assessing theerror bit rate. If no idle message is received, the Remote station automaticallysteps to the next frequency channel maintaining local short term synchronization.The evaluation time is two seconds pe- channel.

3-2

When a call originates from a Master station the idle message is replacedby a call message directed to a specific Remote station. If the Remote stationreceives the call without error, it sends a message to the Master station. If anerror free call message is not received, the sequence will be repeated on the nextfrequency. When the Master station receives a reply to its call, it also analysesthe quality of the message to determine its agreement with the selected frequency.If it agrees, it sends as acknowledgement message or "handshake" to the Remotestat~on. After the "handshake", the Master sends a message to th Remote to ringthe called subscriber. The Remote checks the status of the line and if free ringsthe subscriber. When the subscriber answers, a call connect message is sent to theMaster which switches the call to the HF link. The average time taken to establisha call is 6 seconds with a maximum time for a eight channel system of 16 seconds.The steps taken by the system t, establish a call from the Remote to the Master issimilar to that just described from the Master to the Remote.

For a call between Remote stations, Remot A sends information to the Masteron an idle frequency fl requesting a call to a subscriber at Remote B. The Masterpasses control of the HF network to Remote A which sends a call request on anoth-or frequency f2 to Remote B. If the frequency is acceptable, Remote B sends areply and Remote A checks the reply and if acceptable sends an acknowledgement.Remote A then contacts the Master on fl and indicates the call will be made onanother frequency f2, The Master acknowledges message and returns to idle conditionon frequency on f2. Remotes A and B establish the call over the HF link and returnto the idle condition when the call is completed. on the first clear idle messagereceivedby Remote A an "end of call" message will be sent to the Master who willcheck the message and if acceptable send an acknowledgement.

The data channel is in continuous use while the system is in operation andits performance is critical to the reliable operation of the system. The data

channel uses a 75 bps modem employing binary FSK (85 Hz) shift with in band freq-uency diversity using 1105 Hz and 2125 Hz. The reliability of the channel is en-hanced by the use of error detection coding and "stop and wait" ARQ protocol. Thedata channel serves the following functions which occur sequentially and areexclusive:

- Network synchronizatiun and sounding- Call set up- Syncompex control- Call termination.

Details on the message format for the data channel are described by Derbyshire(1982). The data is organized into eight bit units with a minimum message lengthof 48 bits.

The real time channel evaluation involves the Master station transmittinga 48 bit idle message on each frequency every 2 seconds and each Remote stationreceiving and evaluating this message and keeping statistics on the channel qual-ity. The evaluation uses real and pseudo errors detected on the incoming idlemessage. Real errors are accumulated over approximately four minutes with aweighting factor assigned to each measurement so as to follow rapidly changingchannel conditions. When the system is busy, a four minute time period is notof sufficient length to evaluate rea: errors. Under these conditions, am eval-uation technique was selected based upon "psuedo error" analysis of the incomingdata WGooding, 1968). Pseudo error counts are found to be a suitable measure ofchannal quality. An algorithm is also incorporated in RACE to select the bestchannel for HF communications.

Field trials conducted in 1980 and 1981 for Master to Remote station dist-ances of 65, 270, 490, and 96$ kms confirmed the superiority of the dual diversityFSK over the single channel FSK for evaluating the best channel for voice commun-ications. The single channel PSK selected channels with the smallest multipathspreads which were not necessary those with the best signal-to-noise ratio. Thecall completion rate during the test periods was estimated to be greater than98%using a low power transmitter of 100 watts and simple non-directional broadband antennas. The availability of two and three channels for communications areas follows

two channel availability 96%three channel availability 86%

These data on channel availability indicate the RACE system can support severalsimultaneous calls from a Master station. Even though the RACE system does nottake into account non-reciprocity in propagation or different noise and inter-ference levels at both ends of the circuit, it did not appear to be a majorlimitation in the performance of the system.

a

3. IF MESSAGE TERMINAL

A message terminal was developed at the Communications Research Centre inOttawa, Canada to increase the capabilities of existing HF radio systems by permit-ting the transmission of text messages. The message terminal can be connected iirectlyto an existing system with a 600 ohm input/output ports. Codinq and modulation tech-niques are incorporated in the HF data protocol to enable data communications whenpropagation conditions do not permit intelligible voice transmissions.

The system consists of a portable terminal with an alphanumeric keyboard, ahard copy printer and a single line display. The user types in a messaae on thekeyboard which appears on the terminal display panel. The outgoing messajes havea 1280 character buffer memory which hold the prepared text prior to transmission.The message can be corrected, updated or sent immediately. A typical messaae, aboutfour lines in length, can be transmitted and confirmed en both sender and recelverterminals in 40 seconds. The destination terminal receives the incomini messagewith out ooprator assistance. The outgoing and incoming messages are printed bya small hard copy printer in a 80 character by 10 line page format with a one inchgap between pages.

The terminal has a 75 bps dual channel FSK modem. The modem is impementedwith a microprocessor and free from drift, aging and does rot require high preci-sion components. The modem uses frequency diversity for reliable operation of thedevice during selective fading periods. The data transmission occupies 300 Hz ofthe voice channel enabling more than one network to be operational in a 3kHz band-width.

The following types of calls are possible with the message terminal:

a) Selective Call: Each terminal can call any other terminal on the samenetwork, with ARQ protocol. This mode is very reliable for error freemessages.

b) Broadcast Call: All terminals recognize the global address but do notanswer the call. The message is transmitted several times and the ter-minals accept correct parts of the message. This mode is not as rol-ableas the selective type of call.

c) Privac Call: When this option is selected, the terminal asks for thepassword whh is used to start data randomization operation. Thedestination terminal upon receipt of this type of message only displaysthe calling stations call sign and "ENTER PASPWORD". The incorrect entryof the password lets the operator try three times and then erases the com-plete message. The correct entry of the password performs inverse of therandomization operation and printing of the message.

The terminal has a RS-232 port for external equipment connection of the

following equipment;

a) CRT and printerb) Telephone line or short haul modem for remote controlc) Mass storage facilities

The message terminal increases the capabilities of existing HF radio systemsto transmit short text messages. The terminal can be connected easily to mostconventional HF systems. Modulation and coding are built into the data link protocolto allow data communications under conditions that do not permit intelligible voicecommunications. The terminals allow for unattended reception of messages and option-al communications privacy.

REFERENCES

Chow S.M., and McLarnon B.D., " Syncompes-a Voice Processing System for Low CostHF Radio Telephony", Telecommunications Conference Proceedings, Honolulu, 1981.

Chow S.M., and McLarnon B.D., Real Time Channel Evaluation in an Automatic IIFRadiotelephone System", HF Communication stems and Techniques Conference, London1982.

Derbyshire E.W., "An Automatic Fully Interconnected IF Radio Telephone System"Canadian Marconi Company Brochure, Montreal 1982.

Jull G.W., Doyle D.J., Irvine G.W., and Murray J.P., "Frequency Sounding Tech-niques for HF Communications over an Auroral Zone Path", Proc IRE 50,1962.

Gooding D.J., "Performance monitor Techniques for Digital Receivers Based onExtrapolation of Error Rate", IEEE Trans Communication Technology COM 16,June 1968.

Stevens E.E., "The CHEC Sounding System" Ionospheric Radio Communications: Ed.K.Folksted, Plenum Press, New York,1968.

134

ACKNOWLEDGEMENTS

I wish to thank S.M. Chow of the Communications Research Centre for providingunpublished material on RACE and the HF Message Terminal.

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MODERN HF COMMUNICATIONS

This Bibliography with Abstracts has been prepared to support AGARDLecture Series No. 12"7 by the Scientific and Technical Information Branchof the US National Aeronautics and Space Administration. Washington.I).C., in consultation with the Lecture Series director. I)r J.Aarons, otBoston University. Boston, Massachusetts, USA.

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RE PORT l)OCL MINT*TION P.AGI

1. Recipient'% Reference 2. Originator's Reference 3. Further Reference 4. Securit\ (lTimsficationof I).culnicn t

AGARI-L-S-l 2 ~ ISBN 92-835-1450-5 UNCLASSll:1ll1)

5. Originator Ad1visory) Group for Aerospace Research and I )evlopnment

North A\tlant ic Treaty Organizationi ruc Ancelle. 02200) Neujily Stir Scine. France

6 Title

MoI)E RN I IF COMM LJNICATIONS

-Prewnited at I Lecture Series Under the sponsorship of' the Electromagnetic Wave PropaigationPanel and the Consultant and FExchiange Programme of' AG.\RI onl 30 3 1 \I ay I ON~ in At liens.(rcec onl 2 3 J line 1983 in Romne. I taly and On 14 15 JLine 1983 in Fort %I onmnouth. N.J., US.8. AiLItiorl[Editort s 9 D~ate

Various \lav 983

tO.iior'tFlitor', U~dress I Ipae

Various INS

12. )istribu tion S tatet it Thiis docu menit is diJstribuLted in accord ance withI \ARI)

Policies a iild regulat ions, Which are outli ned Onl tileOutside Black Covers of' all M ( .\ RI) bition's.

13I Kc ,ords lDescriptor,

HIighi frequle ncies COM n iln In ltio n theory'Telecommunication Radio equipment

14.Abstract

Lecture Series 127 is concerned with high frequency Coln IIunIciat ions and is sponsored 1'\tlie IFle t romlagnet ic Wave Propagation Panel o \G \tNRI) a nd im plemen ted by t h' Consul tantand F xcliange lProgramtme.

'Flie aiml o1'fithe lectures is to survey problems and progress in the field of' lIECOMMUNICATIONS. The lectures cover needs of1 bothl the civil and military communitiesfor high frequency communificationls. Concepts of' real time channel evaltiation. systemndesign, as well as advances in equipment. in propagation. and in coding anid modulationtechiniqueIs are covered. The lectures are aimed to bring tion-specialists in this field ipI to dlateso that III COMMUNICATIONS can be considered as a viable technique at this time. [hleproblems. difficulties and limitations of hIF will also be outlined.

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