1

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.

566 MIPRO 2020/CTI

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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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