EVALUATION OF A TERRAIN-BASED POINT-TO-POINT
PROPAGATION MODEL IN THE 900 MHz BAND
f. lazarakis*, a. a. alexandridis, k. dangakis and p. kostarakis Institute of Informatics and Telecommunications, N.C.S.R. “Demokritos”, Greece
and g. s. tombras
Laboratory of Electronics, Department of Physics, University of Athens, Greece
SUMMARY
The accuracy of a semi-empirical point-to-point propagation model, based on terrain data information close to the receiver, is tested. The evaluation is performed through extended transmission loss measurements taken in an urban environment ( Athens region) in the 900 MHz band. The prediction error is calculated for each measurement point and coordinated with detailed terrain information. Specifically, the evaluation of the model is separately performed for various categories of measurement data with respect to the measurement point’s effective height and line-of-sight conditions. 1997 by John Wiley & Sons, Ltd.
Int. J. Commun. Syst., 10, 65–71 (1997)
No. of Figures: 5 No. of Tables: 3 No. of References: 9
key words: mobile communications; propagation model; terrain database
1. INTRODUCTION above-mentioned semi-empirical model by
pro-cessing and statistical analysis of propagation
Mobile radio prediction models have been studied
measurements that form a second set of data, for for over 40 years as a topic of special interest in the
the same test area and the transmitting antenna area of mobile communications. The development of
located at a different site. Moving the transmitting reliable prediction models has been proved to be
antenna to a new location, every reception point has essential for designing and installing a mobile
cellu-a totcellu-ally new pcellu-ath profile. Nevertheless, building lar radio system, especially for areas characterized
environmental characteristics and other parameters by non-uniform terrain and environmental features.
related to the specific urban environment remain To achieve this end the acquisition of field strength
unchanged. The aim of the processing of the new or signal loss measurements is necessary for
study-data set is, first, to test the accuracy and applicability ing the impact of a mobile environment on signal
of the previously mentioned prediction model. variations.
Second, to enrich the available signal measurements During the past, the use of terrain and
environ-set for extensive statistical analysis and improvement mental databases, updated for a specific area, has
of the prediction model for the region of Athens. been addressed as a necessity for the detailed
analy-A summary of the results presented in Reference
sis of signal variations.1–5 In References 4 and 5
5 is given in Section 2 where the data that were the employment of a geographical information
sys-used for the derivation of the propagation model tem (GIS) has been presented for the coordination
will be referred to as the first set of measurements. of measured signal values with detailed
topograph-Moreover, the criteria to be used in this paper for ical data, forming a propagation and topographical
the evaluation of the model are set out at the end information database. The integrated procedure had
of the section. The detailed evaluation of the model been proved to be particularly user-friendly, offering
by means of the new (second) data set is analysed simplicity in estimating crucial propagation
para-in Section 3. meters. On the basis of extended measurements in
the 900 MHz band, taken in the region of Athens,
a semi-empirical model had been developed for the 2. OVERVIEW OF THE FIRST SET OF
MEASUREMENTS specific area.5
In this paper, we examine the validity of the
Propagation measurements are obtained by means of a measuring system. This consists of a mobile unit for signal reception and the recording and stor-*Correspondence to: F. Lazarakis, Institute of Informatics and
age of instantaneous signal power values. Through-Telecommunications, N.C.S.R ‘Demokritas’, GR-153 10, Aghia
Paraskeui, Athens, Greece. Email: fotisl@iit.nrcps.ariadne-t.gr out the measuring procedure, loss deviation, local
CCC 1074–5351/97/020065–07 $17.50 Received December 1996
mean, median transmission loss and location varia-bility information are available. The system operates in full coordination with a GIS, providing, for each reception point, topographical information together with local mean value. Following the guidelines in Reference 6, an unmodulated carrier, at 888 MHz, of known and fixed power, was transmitted from an appropriately sited base unit. A total of 16,351 measurement points was obtained, covering an area extending up to 6 km from the transmitting antenna. 2.1. Derivation of the prediction model
Based on the signal loss measurements obtained
from the procedure described above, a semi-empiri- Figure 1. Comparison of measured and predicted loss for the
cal point-to-point prediction model has been derived. total of measurement points of the first data set
This model is based on detailed topographical infor-mation in order to return a prediction value for each
measurement point. A parameter that best describes model, indicating the general trend of the model to
overestimate (negative value of average prediction local topographical features close to the receiver is
the effective transmission antenna height or the so- error) or underestimate ( positive value of average
prediction error) path loss. The standard deviation
called, effective height (heff).7 An analytical
expression for effective height estimation using ter- of the prediction error represents the model’s
deficiencies if the systematical error is removed. In rain morphology data, can be found in Reference 5.
Considering the definition of heff, a negative heff Reference 9, it is noticed that current models, based
on terrain data and without environmental infor-value practically means a non-line-of-sight (NLOS)
path because of local terrain morphology and high mation, appear with a standard deviation of error in
the range from 6 dB up to 12 dB. Considering the slope values. A different manipulation of
measure-ment points relative to the heff sign, should thus be model under discussion, an average error of 0·8 dB
and a standard deviation of 9·73 dB have been established. The proposed point-to-point prediction
model, introduced in Reference 5, therefore includes obtained. Therefore, although the model does not
take into account obstructions that interrupt line-of-two expressions:
sight ( LOS) from the receiver, its accuracy proves that terrain morphology, close to the receiver, plays
loss (dB)=31·52+40 log(d)
an important role in propagation loss.
−20 log(heff), heff. 0 (1a)
and 3. SECOND SET OF MEASUREMENTS—
MODEL EVALUATION
loss (dB)=55+20 log(d)
+10 log(uheffu), heff , 0 (1b) A second set of propagation measurements has been
obtained for the same region of Athens, with the transmitting antenna installed at a new location. The
where d and heff are measured in meters.
For positive heff values, the expression for loss measuring set-up configuration was kept identical to
the one for the first set of data on purpose. A total prediction is a proper modification of the standard
Lee’s model8 in order to apply for the specific area, of 18,838 measurement points was taken. The
three-dimensional terrain elevation map of the area under and thus it is based on a two-ray model. For
nega-tive heff values, loss prediction is obtained through study is shown in Figure 2, where the old and the
new site of the transmitting antenna are indicated. curve fitting of the appropriate measurement points.
Moreover, urban environment and traffic effects are Furthermore, it can readily be seen that the
propa-gation path profiles of the new measurement points embodied as an average factor for the specific
mobile environment. are different from those of the first set of
measure-ments. A comparison of actual and predicted median
transmission loss versus propagation distance is Measurement data collection, acquisition and
pro-cessing have been implemented using an integrated depicted in Figure 1. Nevertheless, the detailed
evaluation of models is usually performed through system, as described in Reference 4, based on the
utilization of a GIS and digital maps of the area the calculation of prediction error, i.e. measured loss
minus predicted loss, for each measurement point. under study. Following the developed model, the
whole procedure makes it easy to produce loss Throughout this paper, the statistical analysis is
given in terms of average and standard deviation of curves and derive predicted loss for each
measure-ment point. Figure 3 depicts a comparison of the the prediction error. The average prediction error
Figure 2. Three-dimensional terrain elevation map of the area under study with indications for the first and the second antenna positions
model is thus performed separately for points with and without diffraction loss. The following analysis, by means of the available terrain database, is based on the detailed projection of the path profile, with a 10 m step for each measurement point. Hereafter, LOS and NLOS, as well as diffraction phenomena terms, will refer only to terrain morphology and not to obstructions by buildings or other human-made structures. Nevertheless, in an urban environment such as the area under study, ‘pure’ LOS communi-cation can rarely be found. However, this does not affect the validity of our analysis because terrain morphology plays a major role in all cases in sig-nal propagation.
In Table 1, the accuracy of the model is tested Figure 3. Comparison of measured and predicted loss for the
total of measurement points of the second data set for LOS and NLOS locations for the first and the
second set of measurements, in terms of average value of prediction error (av) and error standard
distance) between measured and predicted loss deviation (stdev), both expressed in dB. The column
values. Evaluation of the model’s performance can ‘Counts’ indicates the number of the corresponding
then be obtained through prediction error calculation. measurements in each category whereas their
per-The resultant average error is found to be −1·62 dB centage with respect to the total measurement points,
and the standard deviation equal to 11·02 dB. In is shown within parentheses. At this point it should
comparison with the corresponding error values of be noted that, hereafter, the analysis results for the
the first set, the reliability of the model has been first set of measurements will be used only as a
slightly decreased because the standard deviation of reference. The evaluation of the model will be
per-error has been increased by only 1·3 dB. formed by means of the second set of measurements.
Further investigation and detailed processing of As can be seen, when applying the model to the
measurements led to useful results. As mentioned new data set for LOS locations, the average error
above, large terrain obstructions that lie far from increases by 4·6 dB whereas the standard deviation
the receiver and interrupt line-of-sight causing dif- decreases by 0·6 dB. For NLOS locations, the
aver-fraction loss were not taken into consideration in age error increases by 3·9 dB and the standard
dif-Table I. Prediction error for the first and the second set of measurements
Path Counts av (dB) stdev (dB)
1st set 2nd set 1st set 2nd set 1st set 2nd set
LOS 10,358 (63·4%) 13,507 (71·7%) −0·04 −4.68 9·42 8·82
NLOS 5994 (36·6%) 5331 (28·3%) 2·24 6·13 10·08 12·18
fraction loss does not exist the standard deviation ter diffraction phenomena for locations with positive
heff values. For the first data set, it can be proved
of prediction error will assume an acceptable value.
On the other hand, an obvious reduction of the that NLOS locations have a general trend to suffer
more attenuation than the corresponding LOS
model’s accuracy is noticed for locations where
diffraction loss exists. locations. Therefore, because the model has been
developed for points with positive heff unifying
As mentioned in the previous section, the model
under discussion handles, in a different way, NLOS and LOS locations, loss prediction results in
the overestimation of LOS loss and the underestim-locations with positive and negative values of
effec-tive height. For further testing of the model, loss ation of NLOS loss. This is clearly proved by the
statistical analysis for the second set where, for
values with respect to the heff sign and information
for LOS and NLOS conditions will be considered LOS paths, the average error is −4.54 dB (loss
overestimation), whereas, for NLOS paths, it is 8.81 in the following paragraphs.
In Table 2, statistical analysis results of prediction dB (loss underestimation).
Next, the case of negative heffvalues, for LOS and
error are presented for measurements data
corre-sponding to locations with positive heff values, dis- NLOS conditions, is investigated. Statistical analysis
results are summarized in Table 3 for both measure-tinguished according to LOS and NLOS conditions
for both measurement sets in two main categories. ment sets.
According to the definition of heff it could be
The first category includes the majority of the
measurement points, corresponding to LOS locations expected that negative heff values occur at shadowed
parts of the area under study. However, Table 3 with positive heff values. For these points belonging
to the first data set, the average error and standard reveals that, in practice, there is a small number
of measurements in which, under marginal terrain deviation values indicate a good approximation of
actual transmission loss. For the second set, the conditions and due to mobile antenna height, LOS
paths can occur even for negative heff values.
average error increases by 4·15 dB and standard
deviation decreases by 0·35 dB with respect to the Inspecting the analysis results for the first set of
measurements in Table 3, the model approximates first set. Despite the increase of average prediction
error, its value, together with the error standard the actual transmission loss for points with negative
heff and NLOS conditions pretty well, whereas for
deviation, indicates that predicted loss is still in
good approximation with measured loss.9 The LOS paths the performance is worse with an
absol-ute increase of the average error by 2·9 dB and of second category includes measurement points with
NLOS paths and positive heff values. For these the standard deviation by 2·3 dB. This is expected
because the model has been derived through curve points, even for the data for which the model was
originally developed (first set), the average and stan- fitting of measurement points with heff , 0 without
distinction for NLOS and LOS conditions. Among dard deviation of error show a degradation of the
model’s accuracy compared with the first category. these points, locations with NLOS paths are the
majority (71·8%) and thus, for the case of heff ,
A further increase for both statistical values is
observed for the second set, indicating that the 0, the model is more accurate for NLOS than for
LOS paths. This is verified by the second set of model fails for this category of measurement points.
This is expected because the model does not encoun- measurements where, for LOS paths, the model
Table II. Prediction error analysis for locations with heff . 0
heff . 0
LOS NLOS
1st set 2nd set 1st set 2nd set
Counts 9432 ( 57·6%) 12,853 ( 68·2%) 3632 (22·2%) 3590 ( 19%)
av (dB) −0·39 −4·54 4·10 8·81
Table III. Prediction error analysis for locations with heff , 0
heff , 0
LOS NLOS
1st set 2nd set 1st set 2nd set
Counts 925 ( 5·6%) 654 ( 3·4%) 2362 (14·4%) 1741 (9·2%)
av (dB) 3·61 −7·38 −0·62 0·62
stdev (dB) 11·20 8·83 8·90 10·15
overestimates path loss by 7·38 dB. On the other deviation of error = 10·1 dB). In Figure 5(a)
com-parison of the median transmission loss between hand, a fairly good performance is indicated for
points with NLOS conditions with an average error measured and predicted loss values is presented, for
heff , 0 and NLOS paths, as obtained for the
of 0·62 dB and standard deviation of 10·15 dB.
In conclusion, the evaluation of the model can be second set of measurements. In this case, the model
approximates diffraction loss based only on terrain summarized as follows. When diffraction loss does
not exist and effective height has a positive value, morphology close to the receiver. A more accurate
prediction is expected if detailed path profile infor-equation 1a of the derived model will offer a good
approximation to actual transmission loss (average mation is taken into account.
In order to improve the accuracy of the model,
error = −4.5 dB, standard deviation of error = 8·8
dB). Figure 4 depicts a comparison of the median by considering the diffraction loss aspects, we tried
to incorporate in it some known diffraction loss
transmission loss ( versus propagation distance)
between measured and predicted loss values for algorithms based on multiple knife-edge models
(such as the one proposed by ITU). Nevertheless,
heff . 0 and LOS paths, as obtained for the second
set of measurements. Further improvement can be the application of such algorithms resulted in an
unacceptable loss overestimation because a single achieved by processing only the data that
corre-sponds to heff . 0 with LOS conditions. Generally, terrain irregularity is usually taken as a number of
isolated edges. A better approximation of actual for designing a mobile cellular system in an urban
environment, a criterion for the selection of base transmission losses is expected through the
establish-ment of a more realistic criterion for edge determi-station sites should be the establishment of LOS
paths (considering terrain profile) for most parts of nation and selection.
the cell. In these parts, the majority of the points correspond to positive heffvalues and thus the model
4. CONCLUSION under consideration, being sufficiently accurate for
such signal reception conditions, is a useful tool to Evaluation of the model proposed in Reference 5
has been presented based on extensive measurements get an insight into the functionality of the system.
When diffraction loss exists and effective height and statistical analysis of the collected data. The
measurement data were divided into four categories has a negative value, equation 1b of the derived
model will sufficiently approximate measured trans- according to effective height sign and
characteriz-ation of propagcharacteriz-ation path (LOS or NLOS).
Statisti-mission loss (average error = 0·62 dB, standard
Figure 5. Comparison of measured and predicted loss for points with heff , 0 and NLOS path, as obtained for the second data Figure 4. Comparison of measured and predicted loss for points
current interests in mobile communications include
propa-cal analysis of the prediction error for each category
gation models, digital modulation techniques, diversity
was performed. The model is easily implemented in
techniques and fading channels capacity.
many cases of combined urban and rural environ-ments, being reasonably accurate. It enables a suf-ficient approximation of transmission loss in the absence of diffraction loss when terrain morphology forms a positive effective height, and in the presence of diffraction loss when effective height takes a negative value. Further investigation of diffraction phenomena is needed for the case of distant terrain obstructions along the path profile. In particular, a more sophisticated interpretation of terrain data is needed in order to extract the appropriate number
Antonis A. Alexandridis was born
in Rovies, Greece in 1962. He received the diploma in electrical engineering from the Technical Uni-versity of Patras, Greece, in 1985, and the PhD degree from the Univer-sity of Patras, Greece, School of Electrical Engineering, in 1992.
From 1986 to 1990 he was work-ing on his PhD degree in the Digital Communications Lab of the National Center for Science Research “Demokritos”. During this period he was involved with the design and development
of isolated edges to be used by multiple knife-edge
of hardware and simulation software in order to evaluate
models for the prediction of the diffraction loss.
a CDMA voice communication network. Since 1991 he
Moreover, the information on the terrain morphology has been with the Institute of Informatics and
Telecom-close to the receiver has to be taken into account munications of the NCSR “Demokritos”, first as an R&D
because the above analysis proved its importance in engineer in the Digital Communications Laboratory R&D
projects (Stimulation project, Esprit II FCPN project) and
the total propagation loss.
now as a researcher in the Mobile Communications Lab-oratory. His current interests include mobile communi-cations, propagation models, digital modulation techniques, REFERENCES
and specifically, spread spectrum systems and CDMA
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Kostas P. Dangakis was born in
Kavala, Greece in 1950. He received the diploma in electrical engineering from the National Technical Univer-sity of Athens (1973) and the PhD degree from the University of Patras, School of Electrical Engineering (1984).
From 1974 to 1976, during his military service, he worked as an engineer at the Research Center for National Defence. Since 1977, he has been a researcher
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Athens, and is now head of the Mobile Communications
Tombras, ‘A point-to-point mobile radio prediction model
Laboratory. He has been project leader of several mobile
based on effective height estimation for the region of Athens’,
communications R&D projects. His current interests
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Authors’ biographies:
George S. Tombras was born in
Athens, Greece in 1956. He received the BSc degree in physics from the Aristotelian University of Thessa-loniki, Greece, the MSc degree in electronics from the University of Southampton, UK, and the PhD degree from the Physics Department of the Aristotelian University of Thessaloniki, in 1979, 1981, and 1988, respectively.
From 1981 to 1989 he was a teaching and research assistant, working on adaptive delta modulation techniques, and from 1989 to 1991, a lecturer at the Laboratory of Electronics, Physics Department, Aristotelian University of Thessaloniki. During 1985–86, he served his military ser-vice as a research assistant at the Research Center for National Defence. From 1990 to 1991 he was on sabbatical leave at the Institute of Informatics and Telecommuni-cations of the National Center for Science Research “Demokritos”, Athens, where he was involved in various EC cofunded R&D projects related to mobile communi-cation systems. Since 1991, he has been Assistant
Pro-Fotis Lazarakis was born in Pireas,
Greece in 1968. He graduated from the Department of Physics, Aristotle University of Thessaloniki, Greece, in 1990. He is currently completing his work towards a PhD degree in the area of mobile communications. Since 1991 he has been with the Institute of Informatics and Telecom-munications of the National Center for Science Research “Demokritos”, Athens, first as a postgraduate student and now as a
Depart-ment, University of Athens. His current interests include opean Research Center, CERN, in Geneva, Switzerland, he joined “Demokritos” in 1985.
mobile communications, analogue and digital circuits and
systems, as well as electro-acoustics and audio engineering. Dr Kostarakis is actively involved in testing and type approval and he is Lloyd’s registered auditor for ISO 9000 Dr Tombras is a member of IEEE, AES, and the Helenic
Physicists Association. and a member of the total quality forum.
Panos Kostarakis is research
direc-tor at the Institute of Informatics and Telecommunications at the Greek National Research Center, “Demok-ritos”, in Athens, Greece. Dr Kosta-rakis graduated in physics from the Aristotelian University of Thessa-loniki and got his PhD from the University of Strasbourg. After 10 years of working experience in fast electronics and computers in the