Journal of Geographic Information System, 2011, 3, 140-144
doi:10.4236/jgis.2011.32010 Published Online April 2011 (
Copyright © 2011 SciRes. JGIS
A Geographic Information System Applied to Coverage
Maps of 3G Cellular Communications Networks
Jazmín Ponce-Rojas, Sergio Vidal-Beltrán, Marco A. Acevedo-Mosqueda, Montserrat Jimenez-Licea
Instituto Politécnico Nacional, Escuela Superior de Ingeniería Mecánica y Eléctrica,
Sección de Estudios de Posgrado e Investigación, México DF, México
Received January 14, 2011; revised February 1, 2011; accepted February 13, 201 1
This paper shows the procedure to obtain a continuous coverage map based on a collection of power meas-
urements using a Geographic Information System, through satellite photographs of the Professional Unit
Adolfo Lopez Mateos, and a group of punctual samples of the power of the Common Pilot Channel (CPICH);
which is used to estimate the radio communications channel conditions, taken at different positions and dis-
tances. These samples were taken using specialized equipment to obtain georeferenced measurements, and
by a technique of statistical prediction, as the Krige Method, generate continuous coverage maps, making it
possible to know the distribution of power, and therefore understanding the behavior and configuration of a
Base Station, which in third generation cellular systems is also called Node B.
Keywords: GIS, 3G, Coverage Maps
1. Introduction
In the cell phone as all services must comply with the
quality offered to users. That is why designers and ad-
ministrators of wireless networks require an experiment-
tal analysis to determine the performance of networks. In
a cellular scheme, the analysis is done in the coverage
area (cell) that is assigned to the Base Station –also
called Node B-, it is precisely in this area where the ser-
vice provider ensures that the Node B perform properly
the transmission and reception of radio, filtering of the
signal, amplification, modulation y demodulation of the
signal, besides being the interface to the Controller of
Radio Network (RNC). Normally a Node B has a total
average powe r t ran smission of 20 w (43 dBm) [1].
Both the uplink (User Station to Base Station) as the
downlink (Base Station to User Station) are implemented
with WCDMA (Wideband Code Division Multiple Ac-
cess) which is the technique of media access in third
generation cellular networks (3G), through which multi-
ple users access to a channel at the same time, but with a
unique code that identifies (Scrambling Code SC) each
The third generation cellular system operates in a
unique center frequency at which power is the parameter
of network control, and therefore the variable to analyze;
specifically examine the power of the Common Pilot
Channel (CPICH), which transmits a carrier used to es-
timate the channel parameters. It is the physical reference
for other channels, and is used to control power, coherent
transmission and detection, channel estimation, meas-
urement of adjacent cells and obtaining of the SC [2].
Measuring equipment currently available for this pur-
pose is capable of taking grab samples of the power lev-
els at certain points. For adequate coverage analysis re-
quires the proper spacing between measurements, mak-
ing it easy to apply statistical techniques such as Krige
Method that allows power to predict unknown values
from irregularly spaced known values, that is to say
which through georeferenced measurements of power is
possible to estimate the behavior of the any point within
the studied area obtaining continuous coverage maps.
For complete analysis requires the use of a Geographic
Information System (GIS, Geographic Information Sys-
tem) which is an organized integration of hardware,
software and geographic data, designed to capture, store,
manipulate, analyze and display all forms of geographi-
cally referenced information, to solve complex problems
of planning and management to meet specific informa-
tion necessary for a general vision of the area of interest
1.1. Geographic Information Systems
A GIS is a geographic system wich allows the creation of
maps and spatial analysis; is an information system
be-cause it focuses on the management, data processing
previously stored and allows for efficient, repetitive and
standardized spatial consultations, for adding value to the
information maintained; and is an informatics system
with specialized hardware and software that process the
obtained data (spatial databases). The GIS functions as a
database of geographic information that is associated by
a common identifier to graphic objects on a digital map
in this case the CPICH power level. By separating in-
formation into different layers, are stored separately,
allowing to work with them quickly and easily, to gener-
ate new information that could not otherwise be obtained
There are three groups of models of GIS
Vector GIS.
Raster GIS.
Object-Oriented GIS.
1.1.1. Vec tor Model
This model, focus is on the location accuracy of the ele-
ments of the space. To modeling digitally real world en-
tities using three spatial objects: the point, the line and
the polygon on a mapping system. For example, satellite
1.1.2. Raster Model
A studied area is divided into small areas or array of
square cells identical in size, and the “information” is
stored in each bin for each attribute in the database, for
example, contours. A greater number of rows and col-
umns in the grid (higher resolution), will involve more
effort in the process of capturing information and more
computational cost to process it.
1.1.3. Ob jec t -Oriented Mod el
While data modeling vector and Raster model, organize
their information through of layers, object-oriented sys-
tems try to organize geographic information from geo-
graphical object itself and its relationships with others.
Thus, the geographic objects are subject to a number of
processes and are grouped into classes, introducing a
dynamic character to the information in the system. For
this reason, the object-oriented model is more suitable
for situations where the nature of the objects that try to
model is changing in the time and/or space. The key ad-
vantage that allows this data structure compared to the
other is that from a number of parameters in the behavior
of geographic objects is possible to simulate the evolu-
tion. Because it is so versatile, the area of application of
geographic information systems is very broad, can be
used in most activities with a spatial component [4].
That is why precisely this model was used in this pa-
per for analyzing the behavior of the power levels radi-
ated from the Node B to user stations. Adding a layer of
the vector model (Satellite photograph of the study area)
as shown in Figure 1, is to obtain a clear idea of the ob-
stacles in the propagatio n of the signa l.
2. Methodology for the Generation of GIS
To have an efficient coverage analysis, is essential that
the process of creation of the coverage maps meet a set
of basic criteria, ensuring the reliability and usefu lness of
the information contained in the system. These design
criteria are shown in the following sections.
2.1. Data Selection
For this work, the latitud e and longitude were selected as
a geographical reference of the system, and the CPICH
power level as an attribute, because through the meas-
urement of this power level, the user terminal is able to
establish a comparison between the Node B closer, and
decide which of them will provide the best service. This
will allow that the user station know which is the domi-
nant pilot that would define the coverage area.
Figure 1. Satellite photograph of the study area obtained
from Google Earth.
Copyright © 2011 SciRes. JGIS
2.2. Measurement Process
Using a spectrum analyzer, we obtained a total of 1519
measurement, separate approximately three meters, in
the area shown in Figure 1, whose surface is about 0.7
Km2. In each measurement the spectrum analyzer was
placed at a height between 1.10 and 1.30 meters, since it
is the average height to which the user carries his mobile
equipment. To know the location information of each
measurement requires a GPS Antenna (Global Position-
ing System). The measuring equipment requires at least
pick up the signal from four different satellites to ensure
accurate location information of the sample [5].
2.3. Storage or Pre-Processing Data
The measuring equipment has an internal memory,
which allows storing each measurement, and then are
copied either through USB port or by networking com-
puter equipment through Ethernet port. From the files
obtained, the useful information is extracted with an in
program language C++ and settles into a text file as
shown in Figure 2. In which the data are arranged in
descending using criteria column longitude.
2.4. Data Processing
Data processing is performed to obtain useful informa-
tion from data previou sly entered into the syste m. At this
point coverage continuous maps are generated through
EasyKrig which is a software application implement
on MatLab software platform, this makes the prediction
of power levels continuously using Krige Method ini-
tially developed by Daniel G. Krige in an attempt to
more accurately predict more reserves through an algo-
rithm of least squares regression, which from an experi-
mental semivariogram establishing how similar are the
points in space as they are furthest from the Node B.
Subsequently, the behavior of the power is modeled by a
previously known function, which is called the experi-
mental semivariogram. This will evaluate the power of
the CPICH at any point in the simple space. To ensure
the effectiveness of the prediction is needed a validation
process; included in the application of “EasyKrig” (as
shown in the Figure 3) in which the approximation error
is within the acceptance region determined by the vari-
ability of the measurement power.
The number of measurements needed to ensure a cor-
rect prediction of the measured power levels, depend on
the range of variability that this power. That is to say, if
the power is very variable, must make a greater number
of measurements that when the power does not change
quickly. Knowing the function most appropriate to the
Figure 2. Data file format.
Figure 3. Graphical validation process Krige Method using
the software tool “EasyKrig”.
behavior of the measured power level the information is
plotted so that the axes are defined by geographical co-
ordinates, and the power level determines the color
which represents the sample, as shown in Figure 4,
forming the second layer to superimpose.
2.5. Production Data
After data processing, we have two layers; satellite pho-
tography of the study area and the coverage map. These
overlap to produce new data, as obstacles in propagation,
the ratio of distance/attenuation of the signal, radiation
pattern of transmitting anten na, to na me a few. The result
Copyright © 2011 SciRes. JGIS
Copyright © 2011 SciRes. JGIS
Figure 4. Continuous maps of the pow er le vels.
of the overlay is shown in Figure 5.
Because different Base Stations were radiating to-
wards the area of interest, added more layer to GIS, al-
lowing analysis expands the possibilities, because the
process information of each base station in a different
layer, thanks to the measuring equipment can identify
each SC, it is possible to study interference between ad-
jacent cells, as shown in Figure 6.
3. Results
In each layer of the information system were analyzed
separately each of the main base stations that provide
service in the study area. This allowed a deeper analysis.
For example in Figure 5, we can notice that as the signal
collides with building of different heights suffers at-
tenuation proportional to the height of the same. We can
explain why there is an inc rease in power in the upper left
of Figure 5; this is due to the effect of multipath propa-
gation, in third generation cellular systems by the type of
media access is a favorable effect on propagation envi-
ronments contaminated.
Figure 5. CPICH power distribution in dBm.
On the other hand, Figure 6 shows that the Pilot Do-
minance (strongest signal, indicating the possibility of
providing better service) between two base stations with
more influence in the radio signal has a conflict, since
both radiate a power of similar intensity in the same area,
causing the mobile device has a conflict in the choice of
the base station will provide service.
Using a SIG in this work is possible to know the con-
figuration of the segmentation of the base station anten-
nas, as shown in Figure 7. And indirectly shows the ar-
eas where the call will transfer smoothly, because they
will not switch to another base station, just the call is
transferred to another base station sector. Figure 6. Comparison of the coverage area of two Base Sta-
Figure 7. CPICH power distribution for the sectors of the
Base Station identified by the SC 224, 225, 226 [dBm].
4. Conclusions
The rapid growth of cellular networks in Mexico and
throughout the world with the aim of providing more
benefits to users, causing the cell outline is saturated,
creating problems such as interference between base sta-
-tions. Conflict can be avoided with adequate coverage
analysis. It is at this point that GIS are useful, as a per-
fect complement for different types of information about
a specific geographic area to obtain information not pre-
viously known,
As the coverage area of each base station system
for purposes of interference analysis and transfer
Obstacles in the signal propagation,
Multipath propagation effects,
Pilot pollution, etc.
Number of parameters that can be studied depends on
the capabilities of the measurin g equipment, and existing
vector model of GIS for the area in question, such as
satellite images, contour surveys, hydrographic, etc.
5. References
[1] T. Keji, “WCDMA Mobile Communications System,”
John Wiley & Sons, New York, 2002.
[2] L. Jaana and W. Achim and N. Tomás, “Radio Network
Planning and Optimization for UMTS,” Segunda Edición,
Editorial John Wiley and Sons, New York, 2006.
[3] “Geographic Information Systems,”
[4] “Geographic Information System in the Management of
Natural Hazards,”
[5] “Practical Tips on WCDMA Measurements, Application
Note No. 11410-00378,” Rev. B Printed in United States
Copyright © 2011 SciRes. JGIS