https://doi.org/10.37815/rte.v34n3.947
Original articles
Comparison of radio propagation models in five LTE coverage cells i=
n Riobamba
Comparación
de modelos de propagación de radio en cinco celdas de cobertura LTE de Riob=
amba
Brayan Vique<=
/span>1 <=
/span>https://orcid.org/0000-0=
001-6283-0884,
Carlos Bayas1 =
https://orcid.org/0000-0=
002-3037-3954, Martin Escobar1 https://orcid.org/0000-0=
001-7033-2914, Adrián Infante=
1 https://orcid.org/0000-0=
001-8754-9239, Allison Proaño=
1 https://orcid.org/0000-0=
002-8587-2099
1
brayan.vique@espoch.edu.ec, carlos.bayas@espoch.edu.ec, nicolas.escobar@espoch.edu.ec
Sent: 2022/06/19<= o:p>
Accepted: 2022/09/16
Published: 2022/11/30
Abstract
This article performs a comparative analysis of the power intensity levels measured with the Network Cell Info Lite application and the perform= ance of the different propagation models: Log-Normal, Okumura Hata, COST 231, Walfish Bertoni<= /span>, and SUI in the 4G LTE Frequency Band. The study was conducted in five LTE coverage cells located in the southern area of the city of Riobamba. The mo= del that best fits each cell was chosen by means of absolute error analysis, th= us obtaining an empirical correction factor for the proposed models. For the analysis of the absolute error, three measurement campaigns were carried out with 50 samples where the mean value was obtained. After applying the aforementioned models, the Log-Normal model yielded th= e most favorable results, being the one that achieved the best adaptation in Rioba= mba, since the power levels vary in the range (-80; -106) dBm at a coverage area= not exceeding 200m.
=
Keywords: Coverage cells, frequency band, multiscreen diffraction loss, cells and open spatial propagation model, Friis.
Summary: Introduction,
Theoretical Framework, Methodology, Results and Conclusions.
Resumen
Este artículo realiza un análi=
sis
comparativo de los niveles de intensidad de potencia medidos con la aplicac=
ión
Network Cell Info Lite y el desempeño de los diferentes modelos de propagac=
ión:
Log-Normal, Okumura Hata, COST 231, Walfish Bertoni y SUI, en la Banda de
Frecuencia 4G LTE. El estudio se realizó en cinco celdas de cobertura LTE
ubicadas en la zona sur de la ciudad de Riobamba. Se eligió el modelo que m=
ejor
se ajusta a cada celda mediante el análisis de error absoluto, con ello se
obtuvo un factor empírico de corrección para los modelos propuestos. Para el
análisis del error absoluto se realizaron tres campañas de medición con 50
muestras donde se consiguió el valor medio. Después de aplicar los modelos
antes mencionados, el modelo Log-Normal arrojó los resultados más favorables
siendo este, el que logró una mejor adaptación en Riobamba ya que los nivel=
es
de potencia varían en el rango (-80; -106) dBm a una zona de cobertura no
superior a los 200m.
Introduction
The growing demands on mobile services have encouraged many research=
ers
toward achieving multi- services with low latency. To illustrate that, Zhang
(2012) =
=
pointed out that LTE (Long Term Evolutio=
n) is
a standard for high-speed wireless data communications which is maintained =
as a
project of the 3rd Generation Partnership Project (3GPP). In addition, to c=
over
the requirements of the mobile migrations of Internet applications, such as
VOIP, video streaming, music downloading, and mobile TV, LTE networks offer=
the
capacity to tolerate the throughput explosion for the connection from mobile
devices customized to those new mobile applications. A propagation model is=
a
set of mathematical expressions, diagrams, and algorithms used to represent=
the
radio characteristics of a given environment (Bekele, 2017).
In 2004, an initial study of long-term evolution (LTE) was introduced
and viewed as a path for migration to 4G networks (Rao, 2009). With the rap=
id
development of LTE (4G) technology in recent years, 4G terminals like mobile
phones have been widely used for communication. LTE (4G) signals have cover=
ed
indoor and outdoor environments in modern cities. Inspired by the advances =
in
wireless sensing that have enabled a large variety of new applications such=
as
indoor localization (Li, 2016).
LTE aims to increase the speed and capacity of wireless networks by
utilizing signal processing techniques and modulations (Hadi,
2015). 4G technology is supported by the 3GPP (third generation) standard,
which bases its system on IP, that is, it is a system of systems and a netw=
ork
of networks, and is subsequently overcome in the convergence between cable
networks or wireless networks, computers, electrical devices -electronic, I=
CT
among others to provide access speeds between 100Mbps in movement and 1Gbps=
at
rest, but the most important thing is to maintain the quality of service (Q=
oS)
from point to point (end-to-end), with high security to massify the number of additional ser=
vices
in any place betting on having the lowest possible cost (Tomažič,
2009).
Path loss models are sophisticated tools for predicting coverage are=
a,
interference analysis, frequency assignments, and cell parameters which are=
the
basic elements for the network planning process in mobile radio systems (
The Okumura-Hata model is the most widel=
y used
empirical propagation prediction model. In 1980, Hata<=
/span>
introduced an empirical formula for propagation loss that was derived from
Okumura's report to put the propagation prediction method into computational
use in system planning software. The propagation loss is presented in the
simple form A + B log(R), where A and B are functions of frequency and heig=
ht
of the antenna and R is the distance (Y., 1967). This simplicity of the mod=
el
has made it the most widely used propagation prediction model and it is even
standardized for international use (Union, 1995).
The European Cooperative for Scientific and Technical Research
(Euro-Cost) developed the Cost 231 model, in which the Hata
model is extended to the 2 GHz range, covering the VHF and UHF bands. CM is=
a
correction factor to fit the model by extending the frequency range for whi=
ch
the Hata model operates; CM (0 dB) for medium c=
ities
and suburban areas; CM (3 dB) for metropolitan centers; and that correspond=
s to
the equations presented in the Hata model. One =
of the
contributions of this model is to consider losses due to dispersion (Garcia,
2004).
Stanford University Interim (SUI) model derived from Hata,
with corrections for frequencies above 1900MHz. It includes the path loss
exponent, it proposes three different types of terrain: urban, suburban, and
rural. The height of the antenna of the proposed base station is between 10=
and
80 meters, that of the mobile from 2 to 10 meters, and the extension of the
cell from 0.1 to 8 km (Shahajahan, 2009).
The model, proposed by Joram Walfisch and Henri Bertoni,
considers the losses produced by the diffractions that occur on the roofs of
buildings (Walfish, 1988). It is a model that d=
oes
not consider the existence of a line of sight between the transmitter and t=
he
receiver, it uses the phenomenon of diffraction to describe the losses suff=
ered
by the signal before reaching the receiver located low above the street. The
contribution of the rays that penetrate the buildings and of those that suf=
fer
multiple diffractions is neglected. The separation between the buildings mu=
st
be less than their height and they are supposed to be arranged in parallel
rows. The frequency range in which this model applies is from 300 to 3,000 =
MHz,
with a separation between transmitter and receiver of 200 to 5,000 m. It is=
not
applicable when the base station antenna is below the average height of
buildings (Hernando, 2013).
The log-normal distribution is a function distributing a dependent variable in a normal or Gaussian fashion on a logarithmic scale of the independent variable. This function has been used for a long time to descri= be size distributions of particle properties in atmospheric aerosols. Foitzik (1964) used this functional relationship for = the description of optical aerosol properties. Later, Whitby (1974) built a gen= eral concept for the multimodal nature of the atmospheric aerosol on this approa= ch by fitting measured particle size distributions in a combination of three log-normal distributions (Heintzenberg, 1994).<= o:p>
To determine the performance of the previously proposed propagation models, a comparative analysis of the power intensity levels measured with the Network Cell Info Lite application in the 4G Frequency Band was carried out at 5 LTE coverage cells located in the southern zone of the Riobamba city and the mo= del that best adapts to the conditions of the area will be extinguished by appl= ying an empirical correction factor to the proposed models. The document details= the absolute error for the calculation of this correction factor, considering t= hree measurement campaigns with 50 samples where the mean value was obtained. Fr= om the study carried out, it was concluded that the model Log-Normal is the be= st estimator of power levels considering the environment of the city, which is= a residential area.
Log-Normal Model
It is an empirical model based on a reference of
the losses at a pre-established distance, and applicable in closed environm=
ents
by factors of correction. It is expressed in an equation as a function of t=
he
distance between transmitter and receiver as:
|
|
|
(1)<= o:p> |
Where is the path loss variable due to the mult=
iple
trajectories;
Okumura Hata
Model
The =
Hata
model is an empirical formulation of the graphical path loss data provided =
by
Okumura and is valid from 150 MHz to 1500 MHz. =
Hata presented the urban area propagation loss as a
standard formula and supplied correction equations for application to other
situations. The standard formula for median path loss in an urban area is
given:
|
|
|
(2)<= o:p> |
Where
|
|
|
(3)<= o:p> |
and for a large city, it is given by:
|
|
|
(4)<= o:p> |
|
|
|
(5)<= o:p> |
The predictions of=
the
Hata model compare very closely with the origin=
al
Okumura model if d exceeds 1 km. This model is well suited for large cell
mobile systems, but not personal communications systems (PCS) which have ce=
lls
on the order of a 1km radius (Anonymous, 1968).
Cost 231 Walfish-Ikegami Model
The COST 231 model is a semi-empirical path loss
prediction model. It is recommended for macro-cells in urban and sub-urban
scenarios, with good path loss results for transmitting antennas located ab=
ove
average rooftop height. However, the error in the predictions increases
considerably as the transmitter height approaches rooftop height, leading to
very poor performance for transmitters below that level. Compared to previo=
us
models such as Okumura-Hata, the COST 231 model
includes a series of additional parameters to the calculation process, in
addition to expanding the frequency range in which it can be used (800 - 20=
00
MHz). The model performs a more detailed calculation of the attenuation, ba=
sed
on four additional parameters:
· =
Height of buildings.
· =
Width of streets.
· =
Separation between buildings.
· =
Orientation of the street concerning the
direction of propagation.
For LOS scenarios, the propagation loss conside=
rs
only the free space loss,
|
|
|
(6)<= o:p> |
|
|
|
|
The typical NLOS path described in the COST 231
model is shown in Figure 1
and Figure 2.
Typical NLOS Propagation Scenario Profile view<= o:p>
Typical NLOS Propagation Scenario Top view
The parameters defined in the COST 231 model (<=
/span>Figure 2=
) are t=
he
following:
·
· =
· =
The basic propagation loss for the NLOS scenari=
o is
given by:
|
|
|
|
(7)<= o:p> |
The propagation loss in free space conditions, =
L0,
is obtained according to the expression:
|
|
|
(8)<= o:p> |
The term
The expression for the calculation of
|
|
|
(9)<= o:p> |
where:
|
|
(10)<= o:p> |
The
The multiscreen diffraction loss,
|
|
=
|
(11)<= o:p> |
where:
|
|
|
(12)<= o:p> |
Is a term that depends on the height of the base
station. In addition, the following parameters are defined:
|
|
(13)<= o:p> |
|
|
|
(14)<= o:p> |
|
|
(15)<= o:p> |
The
|
|
|
(16)<= o:p> |
|
|
|
|
|
|
|
(17)<= o:p> |
Walfish-Berton=
i Model
It is valid when there is no line of sight betw=
een
the base station and the mobile. Buildings are modeled as a set of diffract=
ion
and absorption screens buildings of a uniform height and width are consider=
ed,
require that the transmitting antenna is above the highest ceiling.
The path loss is given by:
|
|
|
(18)<= o:p> |
where:
·
·
·
·
Figure 3
Typical
propagation Scenario
The influence of buildings on the signal (Figure 3).
|
|
(19)<= o:p> |
where:
· =
· =
·
In a real environment, the geometry of the
buildings is irregular, causing this model to have less certainty in predic=
ting
the received power; however, this model is applicable in radio propagation
simulation software (Cell View) if adaptations are made to the equations or=
if
an average density and height of buildings are obtained (Shabbir, 2011).
SUI Model
Stanford University
Interim (SUI) model is developed for IEEE 802.16 by Stanford University. It=
is
used for frequencies above 1900 MH. In this propagation model, three differ=
ent
types of terrains or areas are considered. These are called terrain A, B, a=
nd
C. Terrain A represents an area with the highest path loss, it can be a very
densely populated region while terrain B represents an area with moderate p=
ath
loss, a suburban environment. Terrain C has the least path loss which descr=
ibes
a rural or flat area. In , these different terrains and different factors
used in the SUI model are described (Table 1).
Table 1
Different terrains and their parameters
|
PARAMETERS=
|
TERRAIN A<=
b> |
TERRAIN B<=
b> |
TERRAIN C<=
b> |
|
a |
4.6 |
4 |
3.6 |
|
b (1/m) |
0.0075 |
0.0065 |
0.005 |
|
c (m) |
12.6 |
17.1 |
2=
0 |
The pat=
h loss
in the SUI model can be described as
|
|
|
(20)<= o:p> |
where PL represents Path Loss in DBS,
|
|
|
(21)<= o:p> |
where
|
|
|
(22)<= o:p> |
where
|
|
|
(23)<= o:p> |
|
|
|
(24)<= o:p> |
where
|
|
|
(25)<= o:p> |
|
|
|
(26)<= o:p> |
Here,
Figure 4
Location of LTE
coverage cells
The southern area of the=
city
of Riobamba was taken by the Google Maps application where the 5 cells were
located, and the power data was collected for the study of the propagation
models that can be applied in said area. Each antenna works with different
operators (Figure 4).
The applicability of this document was
carried out using 2 software programs: Microsoft Excel for the development =
of
mathematical operations and obtaining numerical data, and MATLAB for the
management of graphs and the statistical study of results.
To determine which model best fits, we=
apply
the equations of the different propagation models considering the correction
factor and the parameters that each model requires.
Coverage Cell =
1
The first cell is located on José Oroz=
co and
Bernardo Darquéa streets from Riobamba City it
belongs to the Tuenti operator and works with an
operating frequency of 1900MHz. Next, the considerations for the use of
propagation models are detailed (Table 2).
Table 2=
Para=
meters Cell 1
|
VALU=
E |
|
|
Base station antenna height =
(m) |
30 |
|
Mobi=
le device height (m) |
1.5<= o:p> |
|
Distance (m)=
|
47–1=
70 |
|
Stre=
et width (m) |
4 |
|
Elevation ang=
le |
14.4=
7°-40.79° |
|
Buildings |
9 |
|
Distance |
4 |
Fuente: <=
span
style=3D'mso-bookmark:_Toc38966068'>https://www2.ulpgc.es/hege/almacen/downlo=
ad/27/27199/propagacion.pdf
Coverage Cell =
2
The second cell is in the Sabún Sports Complex, located on Av. October 9 =
and Atenas street from the Riobamba city, it belongs to
Table 3=
Para=
meters Cell 2
|
PARAMETERS |
VALUE |
|
Ba=
se
station antenna height (m) |
32 |
|
Mobile device hei=
ght
(m) |
1.5 |
|
Distance (m)=
|
48.62 – 205.02 |
|
Street width (m) |
4 |
|
Elevation ang=
le |
20° - 63° |
|
Buildings |
9 |
|
Distance |
3.5 |
Coverage Cell 3
The third cell is located at Celso Rod=
ríguez
Avenue and París street from
Riobamba city, it belongs to the Tuenti operato=
r and
works with an operating frequency of 1900MHz. Next, the considerations for =
the
use of propagation models are detailed (Table 4).
Table 4=
Para=
meters Cell 3
|
PARAMETERS |
VALUE |
|
Base station antenna height =
(m) |
18 |
|
Mobi=
le device height (m) |
1.5 |
|
Distance (m) |
49 – 211 |
|
Stre=
et width (m) |
4 |
|
Elevation angle |
25° - 63° |
|
Buildings height (m) |
9 |
|
Distance between buildings (m) |
4.5 |
Coverage Cell 4
The fourth cell is located at Leopoldo
Freire Avenue and Lisboa Street from Riobamba c=
ity,
it belongs to the CNT operator and works with an operating frequency of
1900MHz. Next, the considerations for the use of propagation models are
detailed (Table 5).
Table 5=
Para=
meters Cell 4
|
PARAMETERS |
VALUE |
|
Ba=
se
station antenna height (m) |
30 |
|
Mobile device hei=
ght
(m) |
1.5 |
|
Distance (m)=
|
49 – 226 |
|
Street width (m) |
4 |
|
Elevation ang=
le |
25°-72° |
|
Buildings |
9 |
|
Distance |
3.5 |
Coverage Cell 5
The fifth cell is located at 9 de Octubre avenue and Noruega street
from Riobamba city, it belongs to the Claro operator and works with an oper=
ating
frequency of 1700MHz. Next, the considerations for the use of propagation
models are detailed (Table 6).
Table 6=
Para=
meters Cell 5
|
PARA=
METERS |
VALUE |
|
Base station antenna height =
(m) |
25 |
|
Mobi=
le device height (m) |
1.5 |
|
Distance (m) |
48.62 – 205.02 |
|
Stre=
et width (m) |
4 |
|
Elevation angle |
17° - 70° |
|
Buildings height (m) |
9 |
|
Distance between buildings (=
m) |
4 |
Finally, the losses obtained by each o=
f the
models mentioned above are replaced in the general formula that is given by=
:
|
|
|
( |
where:
·&nb=
sp;
(=
28)
w=
here:
·&nb=
sp;
·&nb=
sp;
·
Results
Figure 5
Coverage cell 1
without correction factor
=
Figure 5I=
n cell 1
(Figure 5). It is possible to observe that without=
the
corrections to the different propagation models, the samples obtained resem=
ble
the Log Normal model, in addition to the other models such as Okumura-Hata and the Walfish-Bertoni
model, giving results very far from the values measured.
Figure 6
Coverage cell 2
without correction factor
In cell 2 (Figure 6) it is possible to observe that the samp=
les
obtained are similar to the Log Normal model within 100 meters, which is wh=
ere
there is a great concentration of powers, so it can be said that it is wher=
e it
is best has been coupled to the prediction model, considering that the
different attenuations are due to being in an area full of vegetation. On t=
he
other hand, the other models do not coincide with the powers collected beca=
use
the area where the samples were taken does not meet the characteristics of =
the
different models, which is why it is seen that both the Okumura-Hata, Cost 231 and Walfish-Berto=
ni
are far apart with respect to the powers obtained and compared with the data
obtained in the other radio bases, it is observed that these 3 models are m=
uch
further away from each other.
Figure 7
Coverage cell 3
without correction factor
In cell 3 (Figure 7<=
!--[if gte mso 9]>
=
Fi=
gure 8
Coverage cell 4 without correction factor=
In cell 4 (Figure 8<=
!--[if gte mso 9]> <=
/span> Figure 9
Coverage cell 5 without empirical correct=
ion
factor
In cell 5 (Figure 9=
<=
!--[if gte mso 9]>
Next, the graphs of the propagation models
are presented with a correction factor so that they are coupled to the power
measurements of the 5 different LTE coverage cells located in the southern =
zone
of the city of Riobamba, in this way having a prediction of attenuation in =
that
area.
Fi=
gure 10
Coverage cell 1 with correction factor
In cell 1 shown in (=
Figure 10) the correcti=
on
factor was applied to 3 propagation models: Okumura-Ha=
ta,
Cos 231, and the Walfish-Bertoni model, the
correction values were: -20.69 dBm, -13.34 dBm, -21.23 dBm
respectively. When applying the correction factor, the graphs of the
propagation models are better coupled to the power samples taken with the
mobile, however, the model that is more coupled in cell 1 is the Log-normal
model.
In the first 100 meters, many powers were
collected, finally, it was visualized that at a greater distance the samples
suffer an attenuation that is caused by the presence of different
infrastructures. It is possible to observe that, without the corrections to=
the
different propagation models, the samples obtained are =
similar
to the Log Normal model, in addition to other models such as the
Okumura-Hata model and the Walfish-Bertoni
model, giving results very far from those obtained. measured values. Accord=
ing
to Pérez, within his investigation he affirms the following:
A=
ttenuation
as a result of energy absorption by the medium o=
ccurs
as a consequence of the electromagnetic characteristics of the material thr=
ough
which the wave propagates and is the fundamental cause of energy losses in =
the
case of material media. (p. 111). Pérez (2001)
That is why within the first 100 meters
different powers were collected, finally it was visualized that at a greater
distance the samples suffer an attenuation that is caused by the presence of
different infrastructures.
Fi=
gure 11
Coverage cell 2 with correction factor
In cell 2 shown in (=
Figure 11) the correcti=
on
factor was applied to 3 propagation models: Okumura-Ha=
ta,
Cos 231, and the Walfish-Bertoni model, the
correction values were: -30.35 dBm, -19.40 dBm, - 26.20 dBm
respectively. When applying the correction factor, the graphs of the
propagation models performed better than the power samples taken with the
mobile, however, the model that best fits cell 2 is the Log-Normal with
variations less than 5dBm.
In cell 2 (Figure 6) =
it can
be seen that the samples obtained are similar to the Log Normal model
within 100 meters, which is where there is a large concentration of powers,=
so
it can be said that it is where there is a better coupling to the prediction
model, considering that the different attenuations are due to being in an a=
rea
full of vegetation. According to Recommendation ITU-R P.833-3, it states:
In
certain cases, vegetation attenuation may be important, both for terrestrial
systems and for Earth-to-space systems. But the great diversity of conditio=
ns
and types of foliage makes it difficult to develop a general prediction
procedure. In addition, there is a lack of adequately verified experimental
data. (p.1). Recommendation UIT-R P.833-3 (2001)
On the other hand, the other models do not
coincide with the powers collected because the area where the samples were
taken does not meet the characteristics of the different models, so it is s=
een
that both the Okumura-Hata, Cost 231, and Walfish- Bertoni are very=
far
apart concerning the powers obtained and comparing with the data obtained in
the other radio bases, it is observed that these 3 models are much further =
away
from each other.
In cell 3 shown in (=
Figure 12) correction f=
actor
was applied to 4 propagation models: Okumura-Hata,
Cos 231, the Walfish-Bertoni model, and the SUI
model, the correction values were -34.20 dBm, - 27.28 dBm, -3=
4.42
dBm, and -6.69 dBm respectively. When applying the correction factor, the
graphs of the propagation models performed better than the power samples ta=
ken
by the mobile, however, we see that almost all the models fit correctly, be=
ing
the one that stands out the most are the Cos 231 model and the Cos 231 mode=
l.
Log-Normal with differentiation between the measured value and that of the
power of the models not greater than 6 dBm.
=
Fi=
gure 12
Coverage cell 3 with correction factor
In cell 3 (Figure 7=
<=
!--[if gte mso 9]>
=
=
Figure <=
span
style=3D'mso-bookmark:_Ref106524743'>13
Cove=
rage cell 4 with=
correction factor
In cell 4 show=
n in (Figure 13) the correction factor was applied to 3
propagation models: Okumura-Hata, Cos 231, the =
Walfish-Bertoni model, the correction values
were: -31.84 dBm, -14.43 dBm, -20.64 dBm, respectively. When
applying the repair factor, the graphs of the propagation models are better
coupled to the power samples taken by the mobile, however, the curve of the
Okumura-Hata model, together with the normal Log
model, was the most adapted, even though between 140m and 200m there is a
significant dispersion in the measurements whose differentiation is less th=
an 8
dBm.
In cell 4 (Figure 8<=
!--[if gte mso 9]>
In radio systems with low antenna heights,
there are often multiple indirect paths between the transmitter and receiver
due to reflection from surrounding objects, in addition to the direct path =
when
there is a line of sight. This multipath propagation is particularly import=
ant
in urban environments where building walls and paved surfaces generate stro=
ng
reflections. (p.1). Recommendation UIT-R P.1407-1 (2003)
Therefore, the=
y are
far from the results of the models, this is because the data obtained was i=
n a
place full of buildings within the main street.
Figure 14
Coverage cell =
5 with
correction factor
In cell 5 shown in (Figure 14) correction f=
actor
was applied to 3 propagation models: Okumura-Hata,
Cos 231, and the Walfish-Bertoni model, the
correction values were: -30.29 dBm, -21.97 dBm, -29.48 dBm, r=
espectively.
When applying the correction factor, the graphs of the propagation models a=
re
better coupled to the power samples taken by the mobile, however, the one t=
hat
best fits is the normal Log model curve with a differentiation between the
measurements taken and the model less than 5dBm.
One of the technologies and methods used =
is
the repeater or signal amplifier. In this case, the signal received from a
cellular operator is amplified to provide coverage inside a building. The
building or area to be covered can be any building, house, garage, or facto=
ry
where the mobile phone signal is weak, and we want to amplify it. (p.n). Ubierna (2018)
In addition to= the fact that it is possible to observe that there is an intersection between t= he SUI model and Log Normal, this is because these models do not consider loss= es due to reflection from different infrastructures, and within 130 to 135 met= ers the data collected resembles the SUI model.
·
The use of these models and the application of the correction factor
allowed us to analyze the values of reception power and real propagation lo=
sses
in particular environments of the southern zone of Riobamba city.
·
The samples obtained show a significant improvement with the use of =
the
Correction Factor, thus increasing the accuracy of predicting power levels.=
·
In the southern part of Riobamba city, as it is a residential area
without the existence of large buildings, the signal loss does not exceed -=
106
dBm. Despite also the existence of natural topographic factors that influen=
ce
it.
·
According to the results obtained, it was concluded that the Log-Nor=
mal
model is the best predictor of power in the southern area of the city of
Riobamba considering the different scenarios where there were propagation
losses.
·
In the case of using these prediction models in practice, the data m=
ust
be modeled by software to determine the coverage and power of the signal th=
at
the physical equipment must emit.
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5
Comparación de modelos de
propagación de radio en cinco celdas de cobertura LTE de Riobamba