Measurement-based optimized propagation model for urban,...
Transcript of Measurement-based optimized propagation model for urban,...
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Measurement-based optimized propagation
model for urban, suburban and rural
environments for UHF bands in Kosovo Hëna Maloku1, Zana Limani Fazliu1, Mimoza Ibrani1, Myzafere Limani1,2 , Blediona Gashi1
1Faculty of Electrical and Computer Engineering, University of Prishtina, Prishtina, Kosovo 2 Academy of Sciences and Arts of Kosovo, Prishtina, Kosovo
Abstract- Severe spectrum shortage in conventional
bands used for wireless communications has encouraged
an increased interest in researching alternative
frequency bands, which could potentially accommodate
the exponential growth of various wireless technologies.
The ultra-high frequency (UHF) band, traditionally
reserved for TV broadcasters, in particular, has
garnered interest, due to the fact that studies have
consistently shown that the spectrum in this band is
heavily under-utilized. However, in order to study the
true availability of the spectrum and analyze potential
scenarios for opportunistic use, it is necessary to have an
accurate propagation model for the channel. This paper,
derives such a model by using country-wide
experimental spectrum measurements conducted in the
territory of Kosovo, to optimize the parameters of known
propagation models shown to fit the geographical terrain
of Kosovo. The model is extended to encompass urban,
suburban and rural environments. The model is verified
against an additional set of experimental measurement
data and shows a high level of accuracy.
Keywords - TV bands, propagation model, wireless
technologies, parameter optimization
I. Introduction
The development of various wireless technologies and
the spectrum shortage in conventional bands has
encouraged research community to explore alternative
frequency bands. Research has shown that TV band
(UHF frequency band) is severely underutilized [1, 2].
This spectrum band is expected to further increase
with the transition to digital transmission by TV
broadcasters that operate in this band. The path-loss
model plays the most important role in designing a
network and in the parameters of the quality of the
communication links. However, in order to assess the
exact availability in this band for opportunistic usage,
the propagation model that is appropriate for the
country terrain has to be determined first. Previous
study [3] has shown that the path-loss model that best
fits the urban environment in our country is Hata
model for short distances between transmitter and
receivers of a network and Ericsson model for larger
respective distances Since path-loss depends on many
factors including the terrain conditions and
environment, country-wide spectrum measurements
were conducted to derive a model that fits the
geographical terrain of the entire country. In previous
works, empirical propagation models that are based in
measurements have been used to determine the
availability of UHF band in the country. However,
since empirical models are very dependent on the
location terrain, no single model could be best-fit for
the entire country terrain profile. Thus the propagation
model coefficients need to be optimized [4,5,6].
In this work, we have chosen three widely used
propagation models [7, 8, 9, 10] to be considered in
the optimization task using numerical analysis and
simulations in Matlab. The propagation models used
in this work are: Hata, Ericcson and COST 231 model.
The experimental data was collected using NARDA
Selective Radiation Meter SRM-3006 using Spectrum
analysis mode of the device to measure the received
power levels emitted by TV broadcasters in the UHF
band (470-860) MHz [11] and compare them with
simulation results. Optimization of the parameters of
the propagation models shown to fit the geographical
terrain of the country will provide a framework for the
design of future heterogeneous wireless networks that
are envisioned to operate in the TV band.
The rest of the paper is organized as follows: Section
II describes the propagation models chosen to be used
for analytical analysis. The measurement data
collections are presented in Section III. The
optimization process is described in section IV. The
comparative analysis and result discussion is given in
section V with conclusions drawn is section VI.
II. Propagation models description
The empirical propagation models used for
comparative analysis, are described briefly below:
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A. Hata Model
The Hata model is derived from Okumura-Hata model
but is extended for distances 20-100km and it covers
frequency range from 15-1500MHz. Hata’s basic
formulation is given for suburban and rural
environments [12]:
Suburban area:
𝑃𝐿(𝑑𝐵) = 𝑎1 + 𝑎2𝑙𝑜𝑔𝑓𝑐 − 𝑎3𝑙𝑜𝑔ℎ𝑡+ (𝑎4 − 𝑎5𝑙𝑜𝑔ℎ𝑡)𝑙𝑜𝑔𝑅
− 2 [(𝑙𝑜𝑔 (𝑓𝑐28
))
2
+ 5.4]
(1)
Rural area:
𝑃𝐿(𝑑𝐵) = 𝑎1 + 𝑎2𝑙𝑜𝑔𝑓𝑐 − 𝑎3𝑙𝑜𝑔ℎ𝑡+ (𝑎4 − 𝑎5𝑙𝑜𝑔ℎ𝑡)𝑙𝑜𝑔𝑅
− 4.78(𝑙𝑜𝑔𝑓𝑐)2 + 18.33𝑙𝑜𝑔𝑓𝑐 + 40.94
(2)
where, 𝑓𝑐 is the carrier frequency in MHz, ℎ𝑡 base
station antenna height in meters, ℎ𝑟 is the receiver
height and 𝑅 = 𝑟 ∗ 10−3 is the distance between
transmitter and receiver in [km], whereas r is the
respective distance in [m]. The constants
𝑎1, 𝑎2, 𝑎3, 𝑎4 𝑎𝑛𝑑 𝑎5 are model parameters that can be varied according to the environment. Typical values
suburban and rural environments are: 69.55, 26.16,
13.82, 44.9 and 6.55 respectively.
B. Ericsson
The Ericsson model is an extension of Okumura-Hata
model but it allows to adjust the parameters based on
environment. The path loss in this model is calculated
with the following formula :
𝑃𝐿𝐸𝑟𝑖𝑐𝑠𝑠𝑜𝑛 = 𝑎0 + 𝑎1 log(𝑑) + 𝑎2 log(ℎ𝑡)
+ 𝑎3 log(ℎ𝑡) log(𝑑)
− 2(log(11.75ℎ𝑟))2
+ g(f)
(3)
where, f is the carrier frequency in MHz, ℎ𝑡 base
station antenna height in meters, ℎ𝑟 is the receiver
height and d is the distance between transmitter and
receiver in km. The g(f) parameter is defined as:
𝑔(𝑓) = 44.9 log(𝑓) − 4.78(log (𝑓))2
(4)
The values of the constants 𝑎0, 𝑎1, 𝑎2, 𝑎3 for different environments are: Suburban 43.20, 68.63, 12, 0.1 and
Rural 45.95, 100.6, 12, 0.1 respectively [13].
C. COST 231
The COST 231 model is also an extension of Hata
model and its designed to be used in frequency range
from 500-2000 MHz. The expression for the path loss
is given by [14]:
𝑃𝐿 = 𝑎1 + 𝑎2𝑙𝑜𝑔𝑓 − 𝑎3𝑙𝑜𝑔ℎ𝑡 − 𝑎(ℎ𝑟)
+ (𝑎4 − 𝑎5𝑙𝑜𝑔ℎ𝑡)𝑙𝑜𝑔𝑑 + 𝑐𝑚
(5)
where, d is the distance in meters, ℎ𝑡 and ℎ𝑟 are base
station and receiver antenna height in meters and f is
frequency in MHz. Parameter 𝑐𝑚 is defined as 0 dB
for suburban and rural environment. For suburban and
rural environment, the parameter 𝑎(ℎ𝑟) is defined as:
𝑎(ℎ𝑟) = (1.1𝑙𝑜𝑔𝑓 − 0.7)ℎ𝑟 − (1.56𝑙𝑜𝑔𝑓 − 0.8)
(6)
The values for 𝑎1, 𝑎2, 𝑎3, 𝑎4 𝑎𝑛𝑑 𝑎5 are: 46.3, 33.9, 13.82, 44.9 and 6.55 respectively. Although the
frequency range of this model is outside of the
measurements frequency range, the opportunity for
factor correctness made it widely used in the bands of
interest [15].
III. Measurement data collection
Experimental data was obtained from measurements
all over the country. The level of power received from
7 TV transmitters (3 of which are in the capital city of
Prishtina from which 2 are collocated) was recorded in
more than 36 locations with 10 individual
measurements performed at the same location and
lasting for 10 minutes. The power received in 8 MHz
channel was calculated as average of all power levels
detected in 80, 100 kHz wide bins of the same channel.
The locations were chosen such as to represent
different types of environments for different distances
from each transmitter starting from 10-100 km with an
increment of 10km. The choice of the locations was
also constrained by the availability of roads and
accessibility. The transmitter and measurement positions shown are shown in Fig. 1. Transmitter
locations are marked in red, while measurement
locations are marked in yellow color.
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Fig.1. Measurement locations
Since we know the TV transmitter positions [11], as
well as their antenna characteristics and transmit
power, we are able to calculate the distance between
each transmitter and measurement location, and
estimate the measured path loss.
IV. Optimization
The optimization process aims to minimize the root
means square error (RMSE) between the measured
and predicted path-loss values [16]. The measured
path values, for each transmitter, location are obtained
by calculating the difference between transmitted
power from transmitter 𝑡, and the measured power at
location 𝑙 :
𝑃𝐿𝑚𝑡,𝑙 = 𝑃𝑡𝑥
𝑡 − 𝑃𝑟𝑥𝑙
(7)
where 𝑃𝑡𝑥𝑡 is the transmitted power by transmitter 𝑡,
and 𝑃𝑟𝑥𝑙 is the power receive at location 𝑙, in dBm. The
models described in Sec. III, are applied to obtain the
predicted path loss values, denoted as 𝑃𝐿𝑝𝑡,𝑙
.
The optimization problem is therefore formulated as a
minimization of the RMSE values, as follows:
min𝑎𝑖
√∑(𝑃𝐿𝑚
𝑡,𝑙 − 𝑃𝐿𝑝𝑡,𝑙)2
𝑁
(8)
Where 𝑁 is the number of samples and 𝑎𝑖 are the models parameters that are being optimized.
The performance of standard and optimized
propagation models was analyzed based on RMSE
[17, 18] and error probability:
∆�̅� =1
𝑁∑ ∆𝑥𝑖
𝑁
𝑖=1
(9)
where, ∆𝑥𝑖 = |𝑃𝐿𝑝𝑟𝑒𝑑𝑖𝑐𝑡𝑒𝑑 − 𝑃𝐿𝑚𝑒𝑎𝑠𝑢𝑟𝑒𝑑|
(10)
V. Results
The path-loss values measured and estimated with
three aforementioned propagation models are plotted
with respect to distance for suburban and rural
environments separately. In order to compare the
results and see the scale of correctness in path-loss
values, the optimized model was also plotted in the
same graph. The measured values of path loss are
shown in Fig. 2, with black squares whereas in
different colors (red, yellow, purple, and green) are
shown estimated path-loss when using different
standard propagation models and the optimized model
respectively.
Fig. 2. Measured, estimated and optimized path-loss for
suburban environment
As we can see from Fig. 2, the estimated path-loss
values when applying standard models, are higher than
the measured values because we don’t account for
losses due to shadowing and multipath effects. In the
other hand, the optimized path-loss models fit almost
perfectly the measured data. The optimized values for
each model are shown in Table 1.
The results of model performance for the standard
propagation models and optimized ones are shown in
Table 2.
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Table 1: Optimized propagation coefficients for suburban
environments
𝑎0 𝑎1 𝑎2 𝑎3 𝑎4 𝑎5 Hata / 82.95 30.38 14.35 12.52 7.63
Ericsson 43.30 6.80 13.47 0.13 / /
Cost231 52.72 37.59 13.99 17.89 7.61
Table 2: Comparison of performance of propagation models for
suburban environments
Hata Ericsson COST Optimized
RMSE 44.9059 24.5237 25.4261 4.6031
Δ�̅� 39.6186 21.7405 22.7789 2.5816
Fig. 3. Measured, estimated and optimized path-loss for
rural environment
For the rural environment as well, the optimized path-
loss models fit almost perfectly the measured data, as
shown in Fig. 3. The optimized values for each model are shown in Table 3 below.
Table 3: Optimized propagation coefficients for rural environments
𝑎0 𝑎1 𝑎2 𝑎3 𝑎4 𝑎5 Hata / 81.54 30.96 14.12 12.73 8.06
Ericsson 44.38 6.49 13.10 0.12 / /
Cost231 49.82 40.06 16.43 18.70 8.39
The results of model performance for propagation
models and optimized ones in rural environments are
shown in Table 4.
Table 4: Comparison of performance of propagation models for
rural environments
Hata Ericsson COST Optimized
RMSE 50.0749 27.0817 28.2790 4.0598
Δ�̅� 45.9762 24.9013 26.0998 2.4860
In Fig. 4, we have also plotted the RMSE values with
respect to distance for all propagation models
including the optimized ones.
Fig. 4. RMSE of path-loss for all environments
It is evident from Fig. 4 that for both types of
environments with respect to distance, the Hata model
overestimates the path-loss while Ericsson and COST
231 have similar behavior. For short distances, the
values of RMSE for all models are in the range of
acceptable values (10-15 dB) [19], whereas for larger
distances the path-loss values exceed the acceptable
values. In the other hand, the optimized models show
a great performance especially for larger distances.
VI. Conclusions
The true availability of spectrum is difficult to
determine without the proper propagation model that
best fits the type of environment. In the other hand, the
propagation models are very dependent on the type of
environment and terrain making them difficult to use
for different locations. Therefore, the optimized
version of some of the standard propagation models
applied in literature for similar types of environments,
was developed. The measured and estimated data of
path loss values are compared to the path-loss values
generated from optimized models. From the analysis it
is clear that that the optimized propagation models
have the highest accuracy on calculating the path-loss
in terms of error probability and RMSE values for
suburban and rural environments. The findings from
this study will be shared with the national spectrum
regulatory authorities for planning on future
opportunistic usage of these TV bands.
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ACKNOWLEDGMENT
This work was supported by research project
"Research on the Reusability Possibilities of New
Frequency Bands UHF, VHF and Millimeter Waves
for Wireless Communication Networks in territory of
Kosovo" funded by the Kosovo Academy of Sciences
and Arts.
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