Document text
Bulletin of Electrical Engineering and Informatics
Vol. 9, No. 4, August 2020, pp. 1654~1661
ISSN: 2302-9285, DOI: 10.1159 1/ee1.v914.2020 O 1654
Development of a reliable path-loss model for FM broadcast
reception in office locations
Marco G. Domingo, Prince Kendrick E. Estebal, Geraldine A. Tongco, Gerino P. Mappatao
Department of Electronics and Communications Engineering, De La Salle University, Manila, Philippines
Article Info ABSTRACT
Article history: This paper proposes for the development of a path-loss model to improve
the accuracy in predicting the signal level in office locations for the reception
Received Aug 5, 2019 of FM broadcast. Identifying the factors that affect the signal level
Revised Oct 9, 2019 and eventually developing a model to predict the signal inside buildings will
Accepted Dec 11, 2019 guide engineers in designing a broadcast system. A properly designed
broadcast system will ensure optimum signal penetration in these listening
areas. Further, the developed model can find applications in policy-making
Keywords: on the regulation of FM broadcast stations, both for analog and digital radio
systems. Signal level measurements from three FM broadcast stations have
been made inside eight office rooms in De La Salle University-Manila. With
the three stations utilizing circularly polarized transmitting antennas,
Antenna polarization
Channel modelling
FM broadcast the measurements aim to determine the signal levels of the horizontal
Path loss and vertical components of the received signal. These measured levels are
Path loss model used to determine the effects on the magnitude of the received signal of some
factors, such as signal frequency and polarization, receiving antenna height,
walls, transmitter-receiver distance, etc. Since the developed model is based
on the measured signal levels in the actual office environment, its accuracy
is then better than any of the existing models earlier developed.
This is an open access article under the CC BY-SA license.
Corresponding Author:
Gerino P. Mappatao,
Department of Electronics and Communications Engineering,
De La Salle University,
2401 Taft Avenue, Malate, 0922 Manila, Philippines.
Email: gerino.mappatao @dlsu.edu.ph
1. INTRODUCTION
The signal quality in any wireless communication system has the tendency to experience
degradation due to several factors as the signal is propagated in the channel. The signal level decreases when
the signal experiences different kinds of losses as it travels through a medium such as free space [1].
The signal level also experiences scattering, reflection and diffraction due to objects in the environment [2].
All these effects result to problematic signal reception in receivers affecting the quality of the demodulated
information. Poor quality of demodulated signals results to monaural and hissing sound in FM receivers.
This condition of receiving poor information quality is experienced in the office environment, where a bigger
chunk of FM radio listeners is located. A better understanding of the behaviour of the signal in the listening
area is therefore necessary to address the problem. This paper aims to characterize the FM broadcast channel
in office locations to widen the comprehension on the dynamics of the FM signal in the room and eventually
develop a path-loss model for office locations. With the onset of digital radio broadcasting in the Philippines,
the results of this study will be very helpful in crafting new guidelines and policies on the regulation
and operation of this new broadcast system.
Journal homepage: http://beei.org
Bulletin of Electr Eng & Inf ISSN: 2302-9285 O 1655
FM broadcast service in the Philippines operate in Band II (88-108 MHz) and uses an antenna
system that is basially horizontally polarized (H-pol) [3,4]. However, the National Telecommunications
Commission of the country allowed the use of circularly polarized (C-pol) antenna systems having
a vertically polarized (V-pol) component that is no greater than the H-pol [5,6]. According to the National
Association of Broadcasters (NAB) of the United States, the inclusion of the V-pol component is to improve
the penetrating ability of the antenna system, especially in rugged terrains. Further, the NAB has specific
values for the required signal strength an FM station has to produce within its principal community (usually
in an urban setting) and another signal strength specification in the station’s primary service area.
Also, the NAB has specified the maximum usable signal strength within these areas. These signal
specifications provide a dynamic range of signal levels i.e. to avoid excessive radiation that cause adverse
effects [7-11], but strong enough to provide good signal reception [12]. These signal strength specifications,
however, are the signals outside and not inside the buildings. A knowledge of the amount of signal inside the
listening areas and the amount of signal attenuation will help in determining the ample signal needed for
building penetration. This study is just limited to the measurement of the signal inside identified offices in
the locale as indicated by a spectrum analyser. The measured signal is perceived to be the signal level
including noise and distortion, at a particular frequency under consideration. The main objective of this study
is to determine the factors that have effects on the signal level inside the buildings and to develop a model to
predict the signal level more accurately based on these factors. Since the proposed model was developed
based on the actual measured values in the actual listening environment, its accuracy in predicting the path
loss and the signl level in this specific environment is better than any of the existing models that will be shown
and discussed.
2. RESEARCH METHOD
As shown in Figure 1, the method adopted in this study starts from the measurements of the signal
levels outside and inside several offices in a university. The signals emanate from three FM stations with
Metro Manila as their primary service area. The data measured outside the building are used as the reference
in calculating the loss (attenuation) that a signal underwent as it penetrates the building. The aim of
the measurements done inside the rooms is to gather as many signal levels as can be in different locations,
times (periods) of the day, signal frequencies and polarizations. The data analysis basically aims to determine
the factors or parameters that may have effects on the signal level in the test locations. Based on these
identified factors, a path loss model was developed. Model development involves the determination of
the weigth of each of the identified factors and eventually leading to a path loss model for this specific
listening environment.
Signal
Measurement
.
.
Data Analysis
Path Loss
Model
Figure 1. Simplified methodology adopted in the study
Throughout the measurements, the Advantest R3113 Series Spectrum Analyzer was used to measure
the signal level from three FM broadcast transmitters utilizing a folded dipole receiving antenna that was
constructed and patterned after the Ramsey Electronics Model TM100. It uses a ladder-line twin lead antenna
cable and RG174U thin lead coaxial cable. The broadcast stations are in one common tower, all utilizing
C-pol antenna systems. These stations operate at 89.9 MHz, 94.7 MHz and 103.5 MHz carrier frequencies
and are about 6.3 km away from where the measurements were conducted. The eight office rooms considered
in the study are typical office rooms with concrete walls, dimensions (W x L x H) ranging from
5m x 5m x 3m to 15m x 11m x 4m. These rooms are all located within the campus of De La Salle University
(DLSU) in Malate, Manila. Figure 2 illustrates one of the rooms used in the study and showing the locations
of the test points. In the measurements, the receiving antenna is oriented towards the direction of the
transmitter location at about 80 degrees northeast of DLSU. In each room, there are 540 measurements done,
corresponding to five locations in a room (four corners and center of the room), three vertical locations
(center, floor, ceiling), two polarizations (H-pol and V-pol) , three frequencies (89.9 MHz, 94.7 MHz,
Development of a reliable path-loss model for FM broadcast reception... (Marco G. Domingo)
1656 O ISSN: 2302-9285
and 103.5 MHz) and three times a day (morning, afternoon, evening). The data gathering was conducted
twice in eight offices. The total measurements made in all eight rooms is 4320 all in a clear day.
In this paper, the reference signal is taken from the roof deck of the Henry Sy Sr. Hall (HSSH),
approximately 50 meters high. From this location, a clear line-of-site is established and considered to be
the signal level from outside of each room. From the gathered data, four forms of analyses are presented.
These are polarization, signal level, statistical, and path loss model analyses. The path loss model analysis
is presented using the five of the more popular path loss models, namely: Free Space Path Loss Model,
Hata-Okumura Path Loss Model, Walfisch-[kegami Path Loss Model, Clutter Factor Path Loss Model
and the Hata-Okumura Extended Path Loss Model. Characterization of radio channels can be done with
a certain accuracy by measuring the important parameters and developing the right mathematical models.
Having these, engineers can predict signal coverage, achieve the required data rates, and attain specific
performance attributes of alternative signaling and reception schemes [13-17].
From Right
f K~
= Y
Back Right
mag
Figure 2. Test locations in an office room
The free-space path loss model is a basic radio propagation model for predicting the path loss of
radio signals when it travels from the transmitter to the receiver. It is the attenuation of an electromagnetic
wave that would produce a line-of-sight path that would not pass any obstructions that cause reflection or
diffraction. This model assumes ideal atmospheric conditions. It is dependent on the distance of
the transmitter to receiver and frequency. The equation of free-space path loss is:
PL = 32.45 + 20 Log (d) + 20 Log (f) (1)
where d is the distance in kilometers and f is the frequency in MHz.
The Hata-Okumura (or simply Hata) path loss model is an empirical formula combining the effects
of free space path loss, terrain induced path loss, and extensive measurements or radio propagation losses.
This model is widely used in the industry. It only requires four parameters and the path loss equation of
the Hata model is [18,19].
PL = 69.55 + 26.16 Log(f) — 13.82 Log2(hb) — C + (44.9 — 6.55 Loghb)Log d (2)
Where C = 8.29 (Log 1.54hm)* — 1.1
d is the distance in kilometers, f is the frequency in MHz, hm is the receiver antenna height in meters, hb is
the transmitter antenna height in meters.
The Walfisch-Ikegami path loss model is the combination of the Walfisch-Bertoni model and
the Ikegami model. It is considered as the limiting case of flat edge model when the number of buildings is
enough for the field to settle [20,21]. It is created with respect to the scattering and reflection above and
between buildings. The equation of Walfisch-I[kegami path loss model is:
PL = 42.64 + 26 Logd + 20 Log f (3)
where d is the distance in kilometers, fis the frequency in MHz.
The clutter factor path loss model combines the plane earth loss model with an extra loss parameter.
This model introduces frequency to the plane earth loss. It is based on the Egli model with an equation of [19]:
PL = 40 Log(d) + 20 Log(f) + 20 Log(hb) + Lm (4)
Bulletin of Electr Eng & Inf, Vol. 9, No. 4, August 2020: 1654 — 1661
Bulletin of Electr Eng & Inf ISSN: 2302-9285 O 1657
where Lm = 76.3 — 10 Log(hm) forhm< 10m
Lm = 76.3 — 20 Log(hm) forhm=>10m
d is the distance in kilometres, f is the frequency in MHz, hm is the receiver antenna height in meters and hb
is the transmitter antenna height in meters.
Lastly, the Hata-Okumura extended path loss model is an improvement to the most used empirical
propagation model. The International Telecommunication Union (ITU) did the improvement. It is also
referred to as the Electronic Communication Committee (ECC) — 33 model. The equation for this extended
model [19] is:
PL = Ags + Apm — Gi — G; (5)
where Aj, is free space attenuation, Ap, is basic median path loss, G, is the transmitter height gain factor
and G, is received antenna height gain factor. They are individually defined as
Ars = 92.4 + 20 Log(d) + 20 Log (f)
A, = 20.41 + 9.83 Log(d) + 7.89 Log (f) + 9.56 (Log (f))°
hb 2
G; = Log (559 113.958 + 5.8 (Log (d)) ]
G, = [42.57 + 13.7 Log (f)|[Log hm — 0.585]
where d is the distance in kilometres, f is the frequency in GHz, hm is the receiver antenna height in meters
and hb is the transmitter antenna height in meters.
3. RESULTS AND ANALYSIS
There are 30 measured values for each station from the roof deck of HSSH, 15 each polarization.
The measurements were done from 9:30 in the morning to 4:30 in the afternoon. Table | shows the average
of these measured values. These are the values considered to be the reference in the analysis of all measured
values in the office rooms. From the values, the antenna system of 89.9 MHz station has the V-pol almost the
same as the H-pol (50-50 ratio). However, the antenna systems of the 94.7 MHz and 103.5 MHz stations
have a V-pol that is greater than the H-pol. The eight rooms where the measurements are done are in four
buildings within the university. The rooms are in the ground, second, third, fifth, 14th and 20th floors of
these buildings. The signals measured in the rooms went through a minimum of one wall and a maximum of
four walls from the transmitter.
Table 1. Average line-of-sight signal levels
Frequency H-pol V-pol
(MHz) (dBm) (dBm)
89.9 -43.83 -44.04
94.7 -42.09 -41.00
103.5 -47.90 -46.62
A total of 4320 data samples were collected from the data gathering portion of this study. Using
the the large population of measured samples (4320 in all), data analysis is done four ways as described
earlier. The purpose of these analyses is to determine the factors that have significant effect on the signal
level inside the rooms being considered.
3.1. Polarization analysis
This analysis determines the effect of polarization on the signal level inside the rooms. The average
of the V-pol and H-pol data gathered from the measurements in all eight offices was obtained. Each office
has three values for the horizontal polarization and another three for the vertical polarization. One value
corresponds to the average of the signal strength in different antenna heights, room positions, and testing time
for one frequency. Table 2 shows the average V-pol and H-pol measured signal level in the offices.
Relatively, the value of the H-pol signal is greater than the V-pol value, so basically, the radiators are really
H-pol radiators.
Table 2. Average signal levels in the offices
Frequency (MHz) H-pol (dBm) V-pol (dBm)
89.9 -72.80 -72.86
94.7 -71.69 -71.77
103.5 -72.59 -73.15
Development of a reliable path-loss model for FM broadcast reception... (Marco G. Domingo)
1658 O ISSN: 2302-9285
Table 3 is provided to better appreciate the values and easily compare the two components with
reference to the outdoor values shown in Table 2. The table shows the average attenuation done to the signal
at the three frequencies. The average value is determined by subtracting the values in Table 2 from
the outdoor values. It is observed that the H-pol and V-pol ratios for 89.9 MHz are slightly close.
However, for 94.7 MHz, the V-pol is attenuated more than the H-pol. Finally, at 103.5 MHz, the attenuation
encountered by the V-pol has increased compared to its value in 94.7 MHz. However minimal and can be
tolerated, there is a trend that as the frequency increases, the V-pol component encounters higher attenuation
than its H-pol counterpart.
Table 3. Average attenuation encountered by the signal levels entering the offices
Frequency (MHz) H-pol (dB) V-pol (dB) Difference (dB)
89.9 28.97 28.82 -0.15
94.7 29.60 30.77 1.17
103.5 24.70 26.53 1.83
3.2. Statistical analysis
This analysis determines any correlation between the signal frequency and polarization, time of
measurement, and the receiving antenna height inside an office. The analysis is needed primarily to
determine if there is any relationship existing among the parameters. The “corrcoef” function of Matlab is
used to generate the correlation coefficient matrix of the dataset of parameters. The dataset for each
parameter is taken from the 4320 measured values that were classified according to parameter.
The correlation coefficient matrix returns an n x n matrix of the ‘r’ value of the parameters.
The ‘r’ value is the Pearson’s ‘r’ correlation coefficient which determines the strength of
the parameters. If the ‘r’ coefficient is +0.70 - +1, it denotes a very strong to perfect positive relationship.
As the value goes closer to zero, the strength of the relationship weakens. If the ‘r’ coefficient is 0.3 — 0,
there is no relationship among the parameters [22]. The ‘r’ value may also determine an anti-correlation or a
strong negative linear relationship. This occurs when the ‘r’ coefficient is -0.70 to -1.
In this study, correlation of the frequency, polarization (Py and Py), time, and receiver height are
determined in the test locations. The correlation coefficient matrix generated is therefore a 5x5 matrix.
All the ‘r’ values generated in the coefficient matrices are close to zero as shown in Table 4. Based on this,
the parameters do not have any relationship with each other. Also, time of signal measurement and
polarization have negligible effect on the signal level inside the rooms and therefore do not appear in
the proposed model. Thus, it can be said that there are other factors that have a greater effect on the signal as it
enters an office room.
Table 4. Correlation coefficient “r”
Py Py Time Height Frequency
Py 1.0000 0.8445 -0.0924 0.0643 -0.0010
Py 0.8445 1.0000 -0.0918 0.0779 0.0297
Time -0.0924 -0.0918 1.0000 -0.8155 0.0014
Height 0.0643 0.0779 -0.8155 1.0000 -0.0021
Frequency -0.0010 0.0297 0.0014 -0.0021 1.0000
3.3. Signal level analysis
This analysis aims to determine the effect of the transmitter-receiver distance, antenna height,
frequency and the number of walls that the signal went through from the transmitter. The five test points in a
room are converted into their respective distances from the transmitter. These distances represent the offices.
Each room position, the average signals for each receiving antenna height are graphed against each other.
Thus, three lines per graph can be shown. This is done for each frequency, time and polarization. Hence,
there are 90 plots describing the signal level in the various offices. Plotting the signals in this manner will
help determine if there is a trend in the signals received in a specific position inside an office. The x-axis of
the plot is the distance in kilometers of each office with respect to the transmitter. The y-axis is the average
of the received power in —-dBm.
Evident in the 90 plots is a common shape or line. All plots have the same trend with only the range
of average signals changing by a few dBm. Figure 3 shows a sample of the signal level plotted with
the distance. Because the plots of the average signal revealed a trend, the transmitter-receiver distance has an
affect on the signal level. The office room located at the highest elevation (14th floor of HSSH) registers the
highest signal level. The frequency of the received signal also influences the measured signal level. This was
Bulletin of Electr Eng & Inf, Vol. 9, No. 4, August 2020: 1654 — 1661
Bulletin of Electr Eng & Inf ISSN: 2302-9285 O 1659
confirmed by determining the losses encountered by the signals at different frequencies at common test
points in the different rooms.
Average Power vs. Distance from Transmitter
$5
g
3 80
75
x 70
1
bi)
E 65
i
< 60
6.24 6.26 6.28 6.3 6.32 6.34 6.36
Distance, km
—e— Center Flooring —e—Ceiling
Figure 3. Plot of the signal levels over the distance. Data come from the measured values of the H-pol
component at the center portion of the rooms
In this study, the number of walls that the signal went through from the transmitter to the test
location is determined by counting the number of walls the signal passed through if it is projected straight
from the transmitter to the test location. The attenuation done on the signal by the number of walls on
the signal level is determined by analyzing the measured signals that went through different wall
penetrations. As expected, the number of walls a signal is passing through has a significant effect on
the received signal level.
3.4. Path loss models analysis
In this data analysis, five path-loss models are considered. The calculated path loss is converted to
received power to show the differences in the received signal level of each model considered. The measured
signal levels are varying from -60 dBm to -80 dBm. All five conventional methods of determining the path
loss have inaccuracies compared to the measured values. Of these five models, the best is the Hata-Okumura
extended model whose signal level ranges from -35 dBm to 80 dBm. However, it shows a huge error if
the receiver antenna height is less than 10 m and the error gets bigger as the receiver approaches the ground
level. The four remaining models produce values that are far from the measured signal level values and
therefore produce great errors.
Since even the best path-loss model has limitations, the authors developed a simple model to
improve the accuracy in predicting the signal in the office rooms using the data gathered. Based on
the foregoing analyses, the study identified four factors that have direct effect on the signal level inside
the rooms: receiving antenna height, signal frequency, transmitter-receiver distance and the number of walls
that the signal is going through. The model is, therefore, in terms of these factors. To create the appropriate
model, the least squares fitting approach was used. A linear regression framework was followed to fit
the data into a least squares model. The data are first arranged according to the parameters mentioned above
and then imported into Matlab. The “fitlm” function is then used to create the initial least squares model of
the data. Residuals are then observed and removed to improve the accuracy of the model. After this,
the model is further improved using the “step” function. Parameters are added or removed from the model to
improve its effectiveness. When the appropriate model is created, the coefficients are then obtained to
finalize the model. The final model obtained is:
PL = 32.3069 + (—0.0565 =< h) + (4.8869 x d) + (0.0185 x f) + (3.5571 x w) (6)
Where f is the frequency in MHz, d is the transmitter-receiver distance in kilometres, / is
the receiver antenna height in meters and w is the number of walls. In this model, an attenuation of more than
3.5 dB is introduced by each wall that the signal is penetrating. To show the accuracy of the proposed model,
Figure 4 is provided showing a plot of the calculated signal levels using the developed model and the
conventional models as compared with the measured values. The figure was produced with the distance being
varied while the other parameters (h, f and w) are held constant. As shown, the developed model consistently
approximates closely the measured values. Although ECC — 33 model gives a good approximation but not
quite compared to the developed model. It is also evident in the figure that the least accurate are the Free-
space and Clutter Factor path-loss models. The just described model gives a very good approximation on
the signal path loss inside buildings at FM broadcast frequencies. It can also be used, with lesser accuracy, to
other systems such as the ones described in [23-25].
Development of a reliable path-loss model for FM broadcast reception... (Marco G. Domingo)
1660 O ISSN: 2302-9285
» Q
i Ww
ssi ~ = © thie + +
= 70 pit e+ Pit ++ +
= 60 i ik SU o
= 50 SKF x
g 30 om 2 swe wa S te 3 &ë ce
T 37 K E + =
a EHEJ pes a a f
D a pe CIO
6.2 6.26 6.28 6.3 6.32 6.34 6.36
Distance (km)
eè Measured (H) + Developed Free Space @ HATA
@ Woailfisch-kegam k Clutter Factor xHATA-Oku mur a
Figure 4. Received signal level for as determined by the different models at 89.9 MHz
as compared with the measured values
4. CONCLUSION
The measured received signal levels obtained from the actual experimentation were analyzed. With
the volume of measured data gathered in this study, a suitable model for signal level prediction inside an
office environment was developed. Being developed using the actual received data in the office transmitted
by FM transmitters, the model is the best-fit model in predicting the signal level in office environments for
FM broadcast. The model serves as an important source of information in determining the minimum required
power an FM station must transmit to better serve its service area. It can also help antenna engineers in
the design of antenna systems with the proper radiation characteristics requiring lower transmitter power but
providing the required signal level. For future directives, a more comprehensive study is recommended to
further improve the accuracy of the model. One is to do more tests on the observed increased attenuation on
the V-pol signal component more than the H-pol component as the frequency is increased. Another is
the incorporaton of multipath fading in the model.
ACKNOWLEDGEMENTS
The author would like to thank the University Research Coordination Office of DLSU and
the DLSU Science foundation for the realization of this paper.
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BIOGRAPHIES OF AUTHORS
a
A
K
Marco G. Domingo was born in Davao, Philippines in 1993. He received the B.S. degree in
electronics and communications engineering (ECE) from De La Salle University-Manila,
Philippines in 2014. He studied MSc in Automotive Electronic Engineering at the University of
Brighton, United Kingdom. He is currently a Developing Engineer at Tata Technologies.
Prince Kendrick Estebal was born in Laguna, Philippines in 1994. He received the B.S. degree
in electronics and communications engineering (ECE) from De La Salle University (DLSU)-
Manila, Philippines in 2014. He has been an active member of the Electronics and
Communications Engineering Society of DLSU. He is also a member of Institute of Electronics
and Communications Engineers of the Philippines (IECEP) and Institute of Electrical and
Electronics Engineers (IEEE).
Geraldine A. Tongco was born in Mandaluyong, Philippines in 1993. He received the B.S.
degree in electronics and communications engineering (ECE) from De La Salle University-
Manila, Philippines in 2014. She has been an active member of the Electronics and
Communications Engineering Society of DLSU.
Gerino P. Mappatao was born in Tuao, Cagayan, Philippines. He received the B.S. degree in
electronics and communications engineering (ECE) from Saint Louis University, Baguio City,
Philippines in 1989, the M.S. and PhD degrees in ECE from De La Salle University-Manila,
9 Philippines in 1998 and 2012, respectively. He is currently an Associate Professor of Electronics
and Communications Engineering at De La Salle University-Manila. He authored and co-
authored papers in conference proceedings and journals on antennas, broadcast engineering,
wireless communications and image processing.
Development of a reliable path-loss model for FM broadcast reception... (Marco G. Domingo)