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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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206 IEEE TRANSACTIONS ON EDUCATION, VOL. 41, NO. 3, AUGUST 1998
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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PEREZ-FONTAN AND RABANOS: EDUCATIONAL CELLULAR RADIO NETWORK PLANNING SOFTWARE TOOL 207
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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208 IEEE TRANSACTIONS ON EDUCATION, VOL. 41, NO. 3, AUGUST 1998
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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PEREZ-FONTAN AND RABANOS: EDUCATIONAL CELLULAR RADIO NETWORK PLANNING SOFTWARE TOOL 209
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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210 IEEE TRANSACTIONS ON EDUCATION, VOL. 41, NO. 3, AUGUST 1998
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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PEREZ-FONTAN AND RABANOS: EDUCATIONAL CELLULAR RADIO NETWORK PLANNING SOFTWARE TOOL 211
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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212 IEEE TRANSACTIONS ON EDUCATION, VOL. 41, NO. 3, AUGUST 1998
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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PEREZ-FONTAN AND RABANOS: EDUCATIONAL CELLULAR RADIO NETWORK PLANNING SOFTWARE TOOL 213
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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214 IEEE TRANSACTIONS ON EDUCATION, VOL. 41, NO. 3, AUGUST 1998
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.