educational radio planning software

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204 IEEE TRANSACTIONS ON EDUCATION, VOL. 41, NO. 3, AUGUST 1998

It must be pointed out here that professional planning tools

take much longer computation times to carry out the same

tasks. In some cases, computation requires one full day, and

computers are often left to run overnight. This is due to the fact

that their propagation studies use detailed terrain information

in the form of Digital Terrain Models.

Presently, two versions of the original package are available

by contacting either author; one runs under MATLAB 4

including some C routines as indicated above and the other

version was written in TURBO PASCAL language under DOS.

Both versions can be used in a very straightforward way since

they provide pull-down menus where all commands to carry

out the different phases of the planning process can be easily

found (menus are available both in Spanish and English).

Learning how to use CELLPLAN is a fairly easy task. A

menu-driven program like the one being described here greatly

simplifies the learning process which will take a couple of

hours in front of the computer after a general overview of the

program features and its structure have been provided by the

teaching personnel. Furthermore, already finalized examples

are available on the computer hard disk that can be loaded tosee what the final outcome of the program should look like.

Several alternatives are being considered at the moment

for the upgrade of the tool. One basic requirement is that

the program should fully run under Windows. One possible

alternative is to write the whole package in C or PASCAL

language. A preferred alternative is to use the compilation

options of MATLAB 5. In this case, all the development

advantages offered by MATLAB 5 will still be available for

the easy introduction of new features to the program.

Additionally, new features available in second-generation

cellular systems like GSM, for example, discontinuous trans-

mission, power control, slow frequency hopping, etc., are

being considered for implementation in new versions of thissoftware tool.

II. INPUT DATA USED IN PROFESSIONAL

CELLULAR PLANNING TOOLS

When planning cellular networks such as AMPS, TACS,

NMT, GSM, etc., propagation computations are of paramount

importance. For such calculations the basic input file required

is one describing terrain irregularity. This type of file is

known asTerrain Database(TDB) orDigital Terrain Model

(DTM). These files are grid-oriented, describing the terrain

as a regular mesh of height samples. The resolution of these

databases may vary, with values ranging from 50 50 to

1000 1000 m .Other input data files are those which describe the land-

usage or environmental characteristics of the area being stud-

ied: urban, suburban, rural, etc. This information is necessary

to evaluate the extra losses caused by the surrounding environ-

ment. These additional losses are due to the fact that mobile

antennas are low (1.5 to 3 m) compared to the surrounding

environmental features, that cause blockage or shadowing

events when the mobile terminal travels behind a building, a

tree, or any other feature in the vicinity of the mobile terminal.

Environment information is contained in files known

as Land-Usage Databases (LUDB) or Morphostructure

TABLE ITYPICAL LAND-USAGE CLASSIFICATION

Fig. 1. Road and traffic demand maps.

Databases (MDB). In Table I, a typical land-usage classifica-

tion [2] used in professional planning tools is shown.

Finally, maps containing the forecast traffic demand are

necessary in order to supply more radio channels to those areas

with higher demand (urban areas) than to areas with smaller

demand (rural areas). Files containing such information are

known as Traffic Databases (TrDB).

The educational software tool described in this paper does

not consider a specific region where a cellular network is to

be deployed but, rather, a generic or imaginary region

is assumed. In the examples presented throughout this paper

a study area of 120 120 km has been considered. This

approach does not require the use of TDBs as input files. This

greatly reduces the data load to be handled by the simulation

program. Still, the same principles and planning algorithms

may be used without loss of generality.

In order to account for the terrain influence on radio

propagation, random laws are introduced which try to modelthe decay of the received signal with distance from each base

station.

The study area may be configured at users will by introduc-

ing a road map file showing the main cities, roads, borders,

administrative boundary lines, etc. Finally, by defining a

traffic demand map or Traffic Database (TrDB) with different

densities expressed in Erlangs per square kilometer, the study

region is completely specified.

Fig. 1 represents an example of such a region where a

network planning exercise will be carried out to illustrate the

software output plots (Section IV). In the figure, the main

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PEREZ-FONTAN AND RABANOS: EDUCATIONAL CELLULAR RADIO NETWORK PLANNING SOFTWARE TOOL 205

Fig. 2. Program flow diagram.



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TABLE IICELLULAR NETWORK PLANNING STEPS

roads, towns, and boundary (administrative) lines are shown

together with a traffic map.

In order to reduce the need to handle large data files, instead

of using a separate Morphostructure Database (MDB), the

information contained in the Traffic Database is supplied to the

propagation simulation algorithms. In this way, for example,

high-demand areas are associated to dense urban areas and low

traffic demand areas are associated to open areas. Intermediate

density areas are assumed to be suburban areas.

III. CELLULAR NETWORK PLANNING STEPS

In this section the main algorithms implemented in the

educational software are described. The program structure is

also presented in some detail. Cellular network design may

be divided into several phases which are listed in Table II. In

Fig. 2 a sketch of the flow diagram of the simulator is shown.

Several preliminary studies may be carried out in order

to define the adequate cell radius, transmitter power, etc., at

the start-up phase. A cellular spreadsheet is built into the

program so that several radii, number of channels per cell,

etc., are tested for a given average traffic demand.

At program start-up two menu options are available:

Start the design of a NEW NETWORK.

Introduce a new base stations in an EXISTING NET-WORK.

If the first option is selected, a road map and a traffic map

must be input as well as a set of basic network parameters

(Global Parameters, Table III). Then, the first base station

can be defined. A set of base station specific parameters must

be defined at this point (Table III). The process may continue

with the definition of another base station, the recomputation

of all affected network parameters and the storage of the

new network configuration. Network planning can continue

with the deployment of new base stations some time later

in another planning session (LOAD EXISTING NETWORK

menu option). This simulates the temporal evolution of anetwork in which, as new subscribers use the network, new

base stations must be added.

Also, Mobile Station parameters have to be input to the

program. Each network simulation can only be carried out for

a single type of mobile terminal (vehicle-mounted, hand-held

portable, etc.).

A. Definition of a New base station

In the definition of a new base station step a location is

chosen where no cellular coverage is available or a large traffic

demand is detected which cannot be handled by the currently

installed base stations, that is, the Grade of Service (GOS) is

below the quality standard established for the network

GOS of blocked calls

Blocked call in this context means that all available traffic

radio-channels in a given base station are each handling a

communication and, thus, no channel can be used to accept

a new call.Two methods may be used when selecting the sites for new

base stations. One follows as much as possible the geometric

approach of the classical cellular hexagonal geometry [1] with

some location tolerance. Following this approach, when great

traffic demand is found in a given area, the cell splitting

technique can be used. The program overlays the classical

hexagon geometrical pattern on the simulated planning region

where the cellular network is being deployed. This overlaid

information may be followed to position all new base stations.

Several cellular patterns are available with cell clusters [1]

with different numbers of cells, both omnidirectional and

directive (sector) (Fig. 3).

The other possible approach would be to place base stationswithout following a regular pattern. This is in fact what

happens in most real-life situations. Planning engineers usually

take into account the local characteristics of the area where the

base station will be installed using a good knowledge of the

area and their own engineering experience.

B. Propagation Studies

Once a new base station has been placed in the study area

and its parameters set (power, gain, antenna pattern, effective

height, etc.) a propagation studymust be simulated. In order

to account for the terrain irregularity and other factors without

using a Terrain Database (TDB) file, some randomness mustbe introduced in the process so that cells with irregular shapes

are generated, thus simulating different terrain configurations.

The propagation law used is the classical power law ap-

proach [5]

where is the propagation loss in linear units and may range

from for free space conditions to nearly for urban area

conditions. The exponent is varied randomly inside the pro-

gram (without user control) with azimuth in order to simulate

terrain effects on propagation. Moreover, aGaussian variable

is superposed on the path loss values obtained by using the

propagation law in order to simulate locations variability

due to shadowing/blockage effects and, thus, provide more

realistic propagation computations.

In order to account for clutter losses the Traffic Map is

used as if it were a Morphostructure Database. Additional

mean losses associated to different traffic environments (ur-

ban, suburban, rural, ) [5] are included in the

computations.

The received power model for a given location follows the

expression



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TABLE IIINETWORK PARAMETERS: GLOBAL, BASE, AND MOBILE STATION

Fig. 3. Overlaid cellular pattern for assistance in positioning new basestations.

where is a constant related to the transmitter power and the

propagation conditions, is the propagation exponent,

represents the mean additional clutter losses, and is

the Gaussian variate mentioned above. The propagation law is

schematically illustrated in Fig. 4.For the computation of base station coverages and inter-

ference levels, elementary surface elements or prediction

pixels are defined. In this case, and in order to lower the

computational load, surface elements of 500 500 m were

defined for the example shown in Section IV. Normally,

greater resolutions [2][4] are used in practical planning tools

(250 250, 200 200, 100 100, m ).

Received power levels are computed for each surface ele-

ment as shown in Fig. 5. In the figure, the simulated terrain

irregularity effects may be clearly observed. Fig. 6 shows

another cell shape produced by the randomization mechanism

described above.

For each base station a received power fileis created whichspans over all prediction pixels in the study region (in the

examples, 120 120 m ). Fig. 7 illustrates the structure of the

received power files for the different base stations introduced

in the simulation together with the input files. Pixel-wise

operations may be performed with this data arrangement not

only for propagation calculations but also for cell boundary

computations, interference assessment, etc.

The received power computed for any base station at any

surface pixel may be interpreted as the median value of a

Gaussian distribution with a locations variability (standard

deviation) which depends on the type of environment

where the surface element is located. In the program described

in this paper, for simplicity, a single locations variability value

of 6 dB is assumed for all surface elements.

The consideration of the locations variability parameter al-

lows the computation ofcoverageandcarrier-to-interference

values for different probability levels. For example, in

Fig. 5 a coverage plot is shown for 50% of locations and, in

Fig. 8, a coverage plot for 90% of locations is shown for the

same base station. It can clearly be observed how the coverage

area is dramatically reduced if a higher locations probability

is specified.

C. Cell Boundaries

The following stage in the design of a cellular network is

the definition of cell boundaries. This is shown in Fig. 9(a)

and (b) where it can be observed how the introduction of a

new cell completely changes the shapes of other base stations

previously installed in the area.

Cell boundary definition is a rather complicated issue. It

may be defined in terms of the surface elements belonging to

a given cell. This is the deterministic approach that is followed

in the tool described here where each surface element belongs

to only one cell.However, each surface element (pixel) may be defined in

terms of the probabilities of a mobile in that particular surface

element being assigned to the different base stations [2] in the

cellular network. In this way, a surface element could belong

to several neighboring cells with different probabilities.

Other parameters influencing cell definition are, for exam-

ple, the hand-off algorithm, the power control mechanism,

the type of terminal (vehicle-mounted, hand-held), etc. In the

examples presented in this paper a single mobile terminal type

(vehicle-mounted) is used for all computed examples (Section

IV).

In this simulator a very simple approach to the identification

of cell elements (pixels) was adopted: a surface elementbelongs to the cell providing the highest received signal level

(best server). This computation is carried out on a pixel-by-

pixel basis (Fig. 7) by deciding, for every elementary surface

element (pixel), what base station provides the highest received

power.

D. Number of Radio Channels Required

At this point, the number of radio channels requiredmust

be assessed in order to guarantee theGrade Of Service(GOS)

(blocking probability) established as the network quality stan-

dard. The procedure implemented to carry out this computation



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Fig. 4. Propagation model including random variations.

Fig. 5. Random cell shape produced by the program for 50% of locationscoverage probability.

Fig. 6. Another random cell shape produced by the program.

is the integration of the traffic densities in the TrDB for the

new cell. Once the total number of Erlangs for the new cell is

computed, the number of channels required by the new cell is

computed using the Erlang B formula [6] (Fig. 10).

Fig. 7. Input files, received power files, results files. Pixel-wise operations.

E. Frequency Assignments

The next step consists on the frequency assignment phase.

Two options are again offered to the planning engineer, in this

case, a student using the simulator. One option is to follow the

standard cellular approach [1] usingclusters,sets of channels,

and channel groupsfor large and small cells when splitting is

used. An alternative is to use heuristic techniques based on

the evaluation of a compatibility matrix [2], [7]. The com-

patibility matrix contains the distanceexpressed in number of

channels required for any cell pair. This matrix may be used

then as an input to a heuristic frequency assignment algorithm

[7]. Table IV illustrates the structure of a compatibility matrix.



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Fig. 8. Random cell shape produced by the program for 90% of locationscoverage probability.

(a)

(b)

Fig. 9. (a) Cell boundaries with three base stations. (b) Cell boundaries withfour base stations.

represents the required separation in number of channels

for cells and . represents the channel distance within the

same base station which will be dependent on the selectivity ofthe transmitter combining equipment. In this way, a separation

of channels would mean that the same channels can be used

in both base stations, a separation of would mean that for

the two base stations considered a minimum separation of one

channel is required to keep interference below an acceptable

threshold, and so on.

Several criteria are available for the evaluation of the

compatibility matrix. If a protection ratio threshold

is defined, a thorough study would include a pixel-by-pixel

evaluation of the ratio both in the Base-to-Mobile (down-

link) and Mobile-to-Base (up-link) directions (Figs. 11 and

TABLE IVSTRUCTURE OF A COMPATIBILITY MATRIX

12). Simpler criteria may be used to evaluate the cell-to-cell

compatibility matrix elements in order to reduce computation

time. The program provides the following criteria:

closest interfering point;

worst surface element;

average of the worst interference pixels;

pixel-by-pixel study (Figs. 11 and 12).

The heuristic frequency assignment algorithm [7] im-

plemented in the software carries out a channel orderingprocedure in terms of the difficulty of a channel being assigned

in previous iterations. Those channels having failed to be

assigned are always assigned first when a new iteration starts.

F. Verification of Overall Network Quality

At this point, all planning steps have been completed

except for a verification of the network quality, i.e., the

percentage of locations for which adequate coverage and

carrier-to-interference levels are guaranteed and if the total

GOS is within acceptable limits. In the next paragraphs,

the procedure for the evaluation of interference effects from

multiple sources is summarized in some detail.Interference sources reaching an elementary surface element

are multiple (Fig. 13) and the evaluation of the statistics of the

power sum of all interference sources is not straightforward.

The parameter must be evaluated for all surface el-

ements. A Gaussian distribution may be assumed for the

received interference power from each interferer , where

is expressed in logarithmic units (dBm). The power sum,

however, must be evaluated in linear units, (mW). If

follows a Gaussian distribution, then will follow a log-

normal distribution

(dBm) (mW)

What is sought is the evaluation of the statistics of

It is assumed that the overall interference expressed in

logarithmic units follows a Gaussian distribution

Normal

The detailed procedure for the evaluation of the statistics of

Normal can be found in [8].



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Fig. 10. Pixel-by-pixel evaluation of the total traffic demand in a cell.

Fig. 11. Cell compatibility study. Up-link.

Finally, for the evaluation of the statistics of the carrier-

to-interference ratio for each surface element, knowing

that the statistics of the wanted signal are also Gaussian

Normal

the following procedure is used:

Normal

where

and

This multiple interference algorithm is only evaluated for the

down-link direction for simplicity. Coverage and interference

maps are shown after evaluation for all pixels in the study

region. Also, overall network and cell-by-cell interference

statistics are provided by the program. Other statistical studies

are also provided by the program; for example, the number of

times the available channels are reused, etc.

IV. EXAMPLE OF CELLULAR NETWORK DESIGN

In this section several output plots produced by the program

are presented. The input scenario was already depicted in

Fig. 1, where both the road map (plus towns, administrative



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Fig. 12. Cell compatibility study. Down-link.

Fig. 13. Multiple interference statistics assessment on a pixel-by-pixel basis.

lines, etc.) and the traffic demand map are shown. In order

to place the base stations, a seven-cell cluster pattern with

omnidirectional antennas was overlaid on the study area for

guidance. For those sections of the planning area with larger

traffic densities split cells were introduced (Fig. 3). Fig. 14

shows the actual location of the input base stations and Fig. 15

shows the best server plot for the different cell sites. Frequencyassignments were made using the heuristic technique described

in [7].

In Fig. 16, an interference plot map is presented overlaid on

the road map for reference. Computations have been made for

the whole network in the down-link direction. Fig. 17 presents

the interference statistics for one cell in the form of a histogram

with the number of pixels in the cell with a given

value. Fig. 18 shows a whole network coverage plot overlaid

on the road map for reference. In this example, coverage is

guaranteed for more than 90% of the area considered and more

than 90% of the total traffic demand.

Fig. 14. Location of base stations.

The program may also produce channel usage histograms,tables with the number of channels and which ones are used

in each cell, as well as several other network performance

statistics.

V. BRIEF PROGRAM USAGE DESCRIPTIONIn this section a brief description is given of the differ-

ent menu options available in the program and how they

are related. This will further illustrate how the software

package operates. Three captured computer screens showing

examples of the user-friendly menu system are illustrated

in Figs. 1921. The main menu options are: FILE, BASE

STATION, NETWORK, and QUALITY. The most im-

portant options available in the pull-down menu system are

summarized in Tables V-A and V-B.

All simulations must start and finish by selecting the main

menu option FILE. To introduce/remove/edit a base station



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TABLE V-AMAIN PULL-DOWN MENU OPTIONS: FILE

Fig. 15. Cells in the simulated network.

the BASE STATION option must be activated. This optionincludes the realization of a propagation study from the

new base station. A modification in the cellular network, for

example, the introduction of a new base station, requires the

recalculation of all major network parameters. This is achieved

by selecting the option NETWORK which will preform the

computation of cell boundaries, RF channel requirements,

compatibility matrix, and frequency assignment.

Finally, to verify whether the coverage, interference and

GOS quality is acceptable the QUALITY option must be

activated. This option allows the visualization of network maps

showing coverage, interference and GOS levels for each study

area surface element (pixel) as well as tables summarizing the

overall and cell-by-cell quality of the network.

From this information, it may be concluded that parameter

changes in a given base station or the introduction of new

base stations may be required to achieve the desired network

quality. This is done by going back to the BASE STATION

option in the main menu, thus going back to the beginning of

the planning cycle:

BASE STATION NETWORK QUALITY

BASE STATION

A cellular network planning exercise will start with a blank

study area where no base stations are yet defined. The study

area may be configured by defining a number of roads, towns,

and geographic and administrative limits. Finally, a traffic

demand map shall be input. This traffic demand map will

include a background traffic level. Higher traffic demand areas

can be defined around towns and roads by means of polygons

drawn on the screen with the aid of the mouse.

Each network simulation will start by defining a number ofglobal parametersas indicated in the previous sections which

include the frequency band, the number of available channels,

coverage, interference and GOS objectives, etc.

A simulation may be carried out in different sessions. In an

initial session, the global network parameters, maps, etc., and,

possibly, some base stations may be introduced in the network

being planned. This planning exercise may be stored (CLOSE

NETWORK) on the computer hard disk to be continued at

a later time.

When a new base station (main menu BASE STATION

option) is introduced in the network (its position, parameters,



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TABLE V-BMAIN PULL-DOWN MENU OPTIONS: BASE STATION, NETWORK, AND QUALITY

Fig. 16. Network

plot for two locations probability levels.

etc.) the NETWORK menu option has to be run again to

recalculate all network base stations interrelations and, also the

QUALITY menu option must be called up again to observe

what is the new network quality level in terms of coverage, in-

terference, and GOS probability both at cell and network level.

The program implements a simple Modification Flag Sys-

tem that keeps track of changes carried out in the network,

thus keeping track of Network Configuration changes. For

example, a base station power (EDIT BASE STATION)

may be reduced to allow cell-splitting or a base station

may be converted from omnidirectional to directive (sector)

(EDIT BASE STATION) or even a base station may be

completely removed (REMOVE BASE STATION). Other

modifications that will trigger the Modification Flag System



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Fig. 17. Cell statistics.

Fig. 18. Coverage plot for two locations probability levels.

Fig. 19. CELLPLAN welcome window and main menu.

will be the introduction of a new traffic demand map ( NEW

NETWORK).

These are all realistic events that may occur throughout

network roll-out. For example, a traffic estimation made prior

Fig. 20. FILE, NEW NETWORK, LOAD EXISTING MAP menu option.

to network deployment will most certainly be different from

observed values during network operation. Even during the

lifetime of the network, traffic variations will surely happen.



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Fig. 21. FILE, NEW NETWORK, LOAD EXISTING MAP menu option(continued).

When the modification flag is activated an indication is

made to the program operator that several items have to

be recalculated: cell boundaries, RF channel requirements,

(NETWORK) and finally all network quality parameters

(QUALITY).

VI. CONCLUSIONS

An educational software tool for the simulation of the

engineering steps in the design of a radio cellular network has

been presented. Future telecommunications engineers have the

opportunity of simulating the complete process in the design

of a cellular network since the tool provides the most common

features found in professional planning tools used by network

operators and consultants. The tool implements relevant al-

gorithms which radio engineers must be familiar with such as

multiple interference statistics evaluation, compatibility matrix

development, and heuristic frequency-assignment techniques,

classical cellular layouts, propagation statistics, tele-traffic

theory, etc. This tool is being successfully used in a graduate

course on mobile communications at the Telecommunications

Engineering School, University of Vigo, Spain.

REFERENCES

[1] V. H. Mac Donald, The cellular concept, Bell Syst. Tech. J., vol. 58,

no. 1, pp. 1541, Jan. 1979.[2] M. Kruger and R. Beck, GRANDA program system for radio

network planning, PKI Tech. J., vol. 1, pp. 712, 1991.[3] A. Bajwa, Cellular radio planning tools, inCellular Radio Systems, D.

M. Balston and R. C. D. Macario, Eds. Norwood, MA: Artech House,

1993, ch. 11.[4] J. Kaarre and T. Kajamaa, MONICA. A program for cellular network

planning and data management, Telecom Finland (Mobile Telephone

Services), Aug. 13, 1990.[5] H. Hata, Empirical formula for propagation loss in land mobile radio

services, IEEE Trans. Veh. Technol., vol. VT-29, pp. 317325, 1980.[6] W. C. Y. Lee, Mobile Communications Design Fundamentals. New

York: Wiley, 1993, ch. 8.[7] F. Box, A heuristic technique for assigning frequencies to mobile radio

nets, IEEE Trans. Veh. Technol., vol. VT-27, pp. 5764, May 1978.[8] S. C. Schwartz and Y. S. Yeh, On the distribution and moments of

power sums with log-normal components, Bell Syst. Tech.nical J., vol.

61, no. 7, pp. 14411463, Sept. 1982.

Fernando Perez-Fontan (M95) received the telecommunications engineer-

ing degree from the Polytechnic University of Madrid, Madrid, Spain, in 1982and the Ph.D. degree from the same university in 1992.

He has been with the Department of Communications Technologies, Uni-versity of Vigo, Spain, since 1988. His main interests are in the field of radiopropagation modeling for terrestrial-mobile and land-mobile satellite systems.Currently, he participates in different European Space Agency Projects and inthe Euro-COST 255 Action Propagation modeling for new SatCom servicesat -band and above.

Jose Mara Hernando Rabanos received the telecommunications engineeringdegree from the Polytechnic University of Madrid, Madrid, Spain, in 1967 andthe Ph.D. degree from the same university in 1970.

He was with the ITT Research Laboratories (Madrid) from 1967 to 1969.From 1970 to 1977, he was with the Communications Department of Iberia

Airlines of Spain, where he was engaged in the planning and design ofland-mobile and air-to-ground radiocommunication networks. In 1977, hereturned to the Polytechnic University of Madrid as a Full Professor in theRadiocommunications Department, where he has been working in the fieldof cellular network planning and the development of computerized planningtools for digital cellular networks.

educational radio planning software

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