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International Journal of Electrical and Computer Engineering (IJECE)
Vol. 14, No. 3, June 2024, pp. 2737~2752
ISSN: 2088-8708, DOI: 10.11591/ijece.v14i3.pp2737-2752 2737
Journal homepage: http://ijece.iaescore.com
60 GHz millimeter-wave indoor propagation path loss models
for modified indoor environments
Nidal Qasem, Mohammad Alkhawatrah
Department of Communications and Computer Engineering, Al-Ahliyya Amman University, Amman, Jordan
Article Info
ABSTRACT
Article history:
Received Nov 19, 2023
Revised Feb 5, 2024
Accepted Feb 9, 2024
The 60 GHz band has been selected for short-range communication systems
to meet consumers’ needs for high data rates. However, this frequency is
attenuated by obstacles. This study addresses the limitations of the 60 GHz
band by modifying indoor environments with square loop (SL) frequency
selective surfaces (FSSs) wallpaper, thereby increasing its utilization. The
SL FSS wallpaper response at a 61.5 GHz frequency has been analyzed
using both MATLAB and CST Studio Suite software. ‘Wireless InSite’ is
also used to demonstrate enhanced wave propagation in a building modified
with SL FSSs wallpaper. The demonstration is applied to multiple input
multiple output system to verify the effectiveness of FSSs on such systems’
capacity, as well as the effect of the human body on capacity. Simulation
results presented here show that modifying a building using SL FSS
wallpaper is an attractive scheme for significantly improving the indoor
60 GHz wireless communications band. This paper also presents and
compares two large-scale indoor propagation path loss models, the close-in
(CI) free space reference distance model and the floating intercept (FI)
model. Data obtained from ‘Wireless InSite’ over distances ranging from 4
to 14.31 m is analyzed. Results show that the CI model provides good
estimation and exhibits stable behavior over frequencies and distances, with
a solid physical basis and less computational complexity when compared to
the FI model.
Keywords:
60 GHz band
Frequency selective surface
Indoor wireless
Millimeter wave
Path loss model
This is an open access article under the CC BY-SA license.
Corresponding Author:
Nidal Qasem
Department of Communications and Computer Engineering, Faculty of Engineering, Al-Ahliyya Amman
University
Zip-code (Postal Address): 19328, Amman, Jordan
Email: Ne.qasem@ammanu.edu.jo
1. INTRODUCTION
The 60 GHz band is a perfect choice for achieving the desired goal of obtaining high-speed data
rates with a theoretical upper limit of 6.5 gigabit-per-second. It also provides benefits, such as a 10 W
maximum transmit power, a high level of frequency reuse, and a high level of savings in operations [1]–[3].
When comparing the 60 GHz band with other unlicensed bands, it can be seen that the 60 GHz band provides
much higher data rates. However, it is easily blocked by obstacles, and this places more restrictions on using
it. For example, concrete materials, glass, walls, and the human body can cause large signal attenuation on a
60 GHz band. Thus, the 60 GHz communication band is more suitable for indoor and short-range
environments in which sufficient reflectors are present [4].
The unlicensed 60 GHz band allocates 9 GHz sub-bands, which varies slightly depending on local
regulations. Technical standards divide this band into four 2.16 GHz channels. The 61.5 GHz frequency
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which allocates at the second channel has been selected for this study since it is commonly used as an
unlicensed frequency in different regions and countries [5].
Indoor channel simulations/measurements are vital to understanding path loss (PL) as a function of
distance, and temporal and spatial characteristics, which are crucial in performing system-wide simulations to
estimate network system capacities and overall data throughputs. PL models (PLMs) are very important
models with which to comprehend and study the attenuation of signal propagation from transmitters (Tx’s) to
receivers (Rx’s) and allow accurate channel models to be designed for network simulations, which, in turn,
help in designing communication systems. The most common single-frequency PLMs are close-in (CI) and
floating intercept (FI). Both of these models will be studied in this paper [6].
This study focuses on utilization by suggesting an unprecedented technique that can control the
propagation of the indoor wireless environment of the 60 GHz band by completely reflecting the entire
60 GHz band, keeping it inside the area of interest. This technique uses square loop (SL) frequency selective
services (FSSs) wallpaper in order to provide a more strongly received signal; it does this by increasing the
multipath propagation due to the variety of signal paths. In addition, this research provides a comprehensive
study of indoor propagation at the 60 GHz band by using different scenarios to generate a large-scale PL
model (PLM) for enhancing 5th generation standards at the 60 GHz band. In any case, extensive indoor
propagation simulations at the 60 GHz band are needed in order to accurately characterize and model the
channel needed to design a capable indoor system at this frequency.
This paper is organized as follows: section 2 explains the equivalent circuit model (ECM) analyzes
technique and applies it to the SL FSS wallpaper. As well as it explains large-sale PLMs. Next, section 3
examines the simulation results and discussion. It starts with SL FSS wallpaper, and its transmission and
reflection coefficients, using both MATLAB and CST Studio Suite. Then, demonstrates investigations of
some selected scenarios using ‘Wireless InSite’, these scenarios have been tested based on multiple input
multiple output (MIMO) case. MIMO case is presented and performed both with/without SL FSS wallpaper
to investigate SL FSS wallpaper’s effect on the received signal power, both in the presence and absence of
human bodies. In addition, it presents PLMs results. Finally, section 4 concludes this paper.
2. SYSTEM MODEL
2.1. SL FSS wallpaper
FSSs are planar periodic structures that can be used as a filter for a specific frequency of
electromagnetic waves, depending on the interference caused by the periodic arrays of both dielectric and
conducting materials which makes a frequency selective response [7]–[9]. FSSs, in general, have many
common shapes and geometries, such as a SL, ring, dipole, cross dipole, Jerusalem cross, and tripole. These
types can be in one of four modes; high-pass, low-pass, band-pass, and band stop filter [9]. Most of the
previous studies showed that the SL FSS has the best performance and stability to work within the angular
sensitivity, cross polarization transverse electric (TE) or transverse magnetic (TM) modes, and small band
separation [10]. Thus, the SL FSS shape has been selected for this study.
In order to test SL FSS, ECM has been considered as the simple method. The first usage of ECM
technique and first applied to frequency selective circuits was by Anderson [11]. The advantage of ECM is
that it can quickly characterize the FSS response with varying element dimensions. On the other hand, ECM
cannot be used to predict the performance of sophisticated shapes other than simple shapes like SL FSS [12].
The frequency response in SL FSS is determined by the element dimensions (, , , ), as shown
in Figure 1. Where is the separation period, is the dimension of the loop, is the width of the conducting
strip, and is inter-element spacing. These parameters determine the location of the (resonant frequency).
The parameter controls the FSS angular performance [13]. Previous studies have suggested that a bigger SL
in size is generally effective at a lower and a smaller ensures stable with varying incidence angles [14].
ECM technique imposes that the interaction between incident wave and the FSS is represented as a
wave propagating through a transmission line, with shunt lumped circuit impedances. The shunt impedance
could be inductive or capacitive relying on whether the polarization of the incident signal is parallel or
perpendicular to the strip. As shown in Figure 2, the two adjacent strips are approximated as one strip with
width () equal to (2) [15]. The normalized shunt inductive reactance expression of the inductive strip was
given as in [16]:
(1a)
(1b)
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Figure 1. Array of SL FSS elements
Figure 2. Inductive and capacitive part of the SL FSS shape [9]
The normalized shunt capacitive susceptance expression was given as in (2) [12] by Lee:
(2b)
(2b)
where is the correction term:
(3a)
(3b)
where
(4a)
(4b)
and
(5a)
or
(5b)
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where, θ is the incidence angle, is the wavelength in air at operating frequency, is equal to
2 in this calculation, and is the effective permittivity of the surrounding dielectric substrate that
influences the capacitance value.
Equations, which are presented in this section, have shown that the FSS response is a function of SL
element dimensions, incidence angles, and the dielectric material which holds and gives support for the FSS.
In addition, these equations are valid for] for TE wave incidence and for
TM wave incidence for a given range of incidence angle. The equivalent impedance of the SL FSS is given
by (6):
(6)
Hence, the normalized impedance () for the transmission line circuit, as illustrated in Figure 3, can be
determined by (7):
(7)
By using the matrix, the transmission and reflection coefficients for the SL FSS can be determined. As
it is known that an matrix can represent any given network; based on the parameters, the
transmission coefficient () and the reflection coefficient () can be determined [17]. For example, for a
T-network as illustrated in Figure 3, the matrix is presented by (8):
(8)
The scattering S-matrix is defined as (9):
(9)
whereΔ. For the SL FSS, = = 0 and = as defined in (9). Therefore, based on
(10) and (11), the transmission coefficient and reflection coefficient for the FSS can be evaluated.
Because of symmetry = and = . The matrix can be expressed as a function of and
as (10), (11):
(10)
(11)
Figure 3. Transmission line which can be represented by matrix
2.2. Large-scale PLMs
Large-scale PLMs estimate the attenuation over distance of propagation signals and are vital for
designing communication systems. Different types (deterministic, empirical, and stochastic) of large-scale
PLMs exist, but a measurement-based PLM provides realistic insight into the propagation characteristics of a
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wireless channel [6]. Two types of PLMs are studied in this paper: CI and FI. The CI PLM is defined by the
path loss exponent (PLE) [18]–[21]:
(12)
(13)
where is the wavelength in m, =1, and
is a zero mean Gaussian random variable with standard
deviation given by (14) and (15) [6]:
(14)
(15)
where,, and is the number of measured PL data
points. The CI PLM uses a physically based reference distance, and is the mean PLE, which indicates
how fast PL increases with distance. The FI PLM is currently used in standards work, such as the 3rd
Generation partnership project (3GPP), and can be calculated as (6) [22]–[25]:
(16)
Assume that and the zero mean Gaussian random variable is [6]:
(17)
and the standard deviation is [6]:
(18)
where is the floating intercept and given by [6]:
(19)
and is the slope of the line (different than the PLE) and given by (20) [6]:
(20)
where
is a log-normal random variable with mean 0 dB and standard deviation .
3. RESULTS AND DISCUSSION
3.1. SL FSS (MATLAB)
MATLAB has been used to solve the theoretical equations for ECM for the suggested design of the
SL FSS element; resonance occurs when each half loop acts as a dipole [4,9]. The basic rule of thumb in
designing loop circumference is to make its response approximately equal to the resonant frequency
(61.5 GHz). Basic design rules for SL FSS element dimensions are given along with equations for the ECM.
Where its dimensions are:=1.4 mm, =0.1 mm, =1.2 mm, =0.2 mm,and
= 2. Figures 4 and 5
show the and responses coefficients for the designed SL FSS at a 0° incidence angle, respectively.
3.2. SL FSS (CST studio suite)
CST Studio Suite is used to test and analyze the designed SL FSS parameters. The analyzes method
used is the finite integration technique on Cartesian or tetrahedral grids. As shown in Figure 6, SL FSS has
been tested for a range of different incidence angles from 0° to 60°. The is presented for both TE and TM
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modes, as shown in Figures 7 and 8, respectively. The is also presented for the TE and TM modes, as
shown in Figures 9 and 10, respectively. All of the figures for the transmission and reflection coefficients are
expressed in a range of frequencies from 50 to 70 GHz. Copper with a 0.07 mm thickness is used as the
conductive material. The dielectric material is Arlon AD 300, which has a 0.1 mm thickness and a relative
permittivity value of 3.
Figure 4. The theoretical frequency transmission response of SL FSS wallpaper based on ECM equations
Figure 5. The theoretical frequency reflection response of SL FSS wallpaper based on ECM equations
Figure 6. The SL FSS dimensions, where = 1.4 mm, = 0.2 mm, = 1.2 mm, and = 0.1 mm
In order to evaluate the response of a filter as a band-stop, the attenuation value must exceed -25 dB
at the resonant frequency (61.5 GHz) to kill the signal [9]. As shown in Figures 7 and 8, the transmission
coefficients for both TE and TM modes are more than -25 dB. That means that the signal will be dead when
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trying to penetrate the area of interest. The reflection coefficients shown in Figures 9 and 10 are also smaller
than -0.05 dB at 61.5 GHz, which allows the SL FSS wallpaper to act as a perfect reflector inside the area of
interest, achieving its goal.
Figure 7. The transmission response of SL FSS wallpaper for TE-mode
Figure 8. The transmission response of SL FSS wallpaper for TM-mode
Figure 9. The reflection response of SL FSS wallpaper for TE-mode
Figure 10. The reflection response of SL FSS wallpaper for TM-mode
3.3. Investigation of scenarios using ‘wireless InSite’
‘Wireless InSite’ is used as a tool to evaluate the received power for different scenarios inside the
area of interest. The reflection and transmission coefficient values of the SL FSS wallpaper have been
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exported to ‘Wireless InSite’ in order to obtain the SL FSS wallpaper response. The scenario of interest in a
room with dimension 15×10 m has been investigated. The target scenario investigates a MIMO
communication system with/without SL FSS wallpaper, while MIMO scenario studies two more sub-
scenarios; with/without human bodies.
3.3.1. MIMO system scenario
a. MIMO without SL FSS wallpaper
This scenario contains a 2x2 MIMO communication system for Tx and the Rx’s. Both the Tx and
Rx’s are assumed to consist of two antenna elements spaced by λ/2 [26]. Tx has a directional antenna with
10 dBm input power, 14 dBi gain, 2.5 m height, and 90o HPBW. Rx’s are distributed in 20 locations. Each
Rx has an omnidirectional antenna with a sensitivity of -64 dBm and 1.5 m height.
1) Without human bodies
The 2D and 3D views of this scenario are shown in Figures 11 and 12. Table 1 shows the electrical
parameters of the materials used in this study [9]. Figure 12 shows the 3D view of the first scenario, which
has been studied without using SL FSS wallpaper. The received signal power at each Rx location is shown in
Figure 13.
Figure 11. 2D view for the MIMO scenario
Figure 12. 3D view for the MIMO scenario without SL FSS wallpaper and human bodies
Table 1. Electrical parameters used for building area of interest [9]
Component
Material
Conductivity, ()
Relative Electrical Permittivity,
Thickness ()
Walls
Brick
0.001
4.44
0.150
Ceiling and Floor
Concrete
0.015
15
0.3
Windows
Glass
0
0.003
Doors
Wood
0
0.03
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Figure 13. The received signal power for each Rx location number for the MIMO system scenario without SL
FSS wallpaper and human bodies
2) With human bodies
The 2D and 3D views of this scenario are shown in Figures 14 and 15. The black parallelepipeds
represent the number of human bodies situated randomly in the room. The human body has been modelled
inside ‘Wireless InSite’ based on the complex permittivity values of its basic components; skin, fat, muscle,
and pure water, at a 60 GHz resonant frequency, as summarized in Table 2 [4]. The received power at each
Rx location is shown in Figure 16. Figure 17 shows that the average received power in the MIMO system has
been attenuated by 3 dB, on average, with the presence of human bodies.
Figure 14. 2D view for the MIMO scenario without SL FSS, but with a number of human bodies
Figure 15. 3D view for the MIMO scenario without SL FSS wallpaper, but with a number of human bodies
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Table 2. Complex permittivity at 60 GHz of human body components [4]
Human tissues
Skin
Fat
Muscle
Pure Water (20 oC)
Figure 16. The received signal power for each Rx location number for the MIMO system scenario without SL
FSS wallpaper, but with a number of human bodies
Figure 17. The received signal power for each Rx location number for the MIMO system scenario without SL
FSS wallpaper, but with a number of human bodies
b. MIMO with SL FSS wallpaper
1) Without human bodies
The scenario depicted in Figure 12 is replicated by employing the technique of attaching SL FSS
wallpaper at a distance of /10 from the wall. It is demonstrated in Figure 18. A representation of the
received signal power at each Rx site is shown in Figure 19.
Figure 18. 3D view for the MIMO scenario with SL FSS wallpaper, but without human bodies
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Figure 19. The received signal power for each Rx location number for the MIMO system scenario with SL
FSS wallpaper, but without human bodies
2) With human bodies
Figure 20 shows the above scenario with a number of human bodies added. Figure 21 shows the
received signal power at each Rx location. Figure 22 shows that the received power has been reduced in the
MIMO system scenario with SL FSS wallpaper and a number of human bodies by an average of 2 dB
compared to the scenario without human bodies.
Figure 20. 3D view for the MIMO scenario with SL FSS wallpaper and a number of human bodies
Figure 21. The received signal power for each Rx location number for the MIMO system scenario with SL
FSS wallpaper and a number of human bodies
Figures 23 and 24 show the difference in the received signal power before and after attaching SL
FSS wallpaper at each Rx location for the MIMO system scenario with/without human bodies, respectively.
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In these figures, the received power at each Rx location has been enhanced after attaching SL FSS wallpaper
by an average of 6.87 dB with and 6.53 dB without human bodies. Note that the received power at Rx
location number 5, as shown in Figure 23, has been attenuated due to the beam-width of the Tx, whose signal
suffers more reflections before reaching the Rx.
Figure 22. The achieved attenuation for each Rx location number for MIMO system scenario with SL FSS
wallpaper with/without human bodies
Figure 23. The gain enhancement for each Rx location number between MIMO system scenarios
with/without SL FSS wallpaper with human bodies
Figure 24. The gain enhancement for each Rx location number between MIMO system scenarios
with/without SL FSS wallpaper without human bodies
3.4. Large-scale PLMs
Using the two large-scale propagation PLMs presented in subsection 2.2 and the indoor simulation
data for a 60 GHz band, PL parameters are analyses and compared. The single-frequency CI and FI PLMs
parameters at a 60 GHz band for different indoor scenarios are presented in Table 3 (for the purpose of
comparing PLMs and saving space, only directional antenna for Tx and omnidirectional antenna for Rx PL
data captured with vertically-polarized (V-V) Tx and Rx antennas are included). It can be observed from
Table 3 that the CI model provides intuitive PLM parameter values due to its physical basis, while the
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parameters in the FI model sometimes contradict fundamental principles. For example, for the humans
without SL FSS wallpaper scenario in a non-line-of-sight (NLOS) environment, the CI model generates a
PLE of 3.39, which nearly matches the theoretical free-space NLOS PLE of 4; however, in the FI model, it is
-0.02, meaning that the PL decreases with distance, which is obviously not reasonable or physically possible
in a passive channel.
The resulting single-frequency path loss model parameters emphasize the frequency dependence of
indoor PL beyond the first meter of free space path loss (FSPL), where PLEs in the ring FSS wallpaper
without humans scenarios at 61.5 GHz are larger than the PLEs for the same scenarios, but without ring FSS
wallpaper, as shown in Table 3. Specifically, line-of-sight (LOS) PLEs are 1.46 and 1.7 at 61.5 GHz
with/without ring FSS wallpaper in without humans scenarios, respectively, indicating constructive
interference and waveguiding effects in LOS indoor channels at mm-wave frequencies. Furthermore, the
NLOS PLEs are 3.4 and 2.9 at 61.5 GHz for the same scenarios, respectively, showing that 61.5 GHz
propagating waves attenuate by 10 dB more per meter of distance in the indoor environment beyond the first
meter, as provided in Table 3. For with/without ring FSS wallpaper with humans scenarios, LOS PLEs are
1.5 and 1.76 at 61.5 GHz, respectively, indicating constructive interference and waveguiding effects in LOS
indoor channels at mm-wave frequencies. Furthermore, the same reasons apply to the NLOS PLEs, which
are 3 and 3.9 at 61.5 GHz for the same scenarios, respectively. By using the strongest NLOS received
power path from Tx-Rx (NLOS-Best) PLE reduced to 2.54 and 2.9, which is an important improvement
for NLOS case.
Table 3. Parameters for the single-frequency CI and FI PLMs in a typical modified indoor scenario
Scenario
Pol.
Freq. (GHz)
Env.
Distance Range (m)
Model
PLE/
SL FSS Wallpaper
with Humans
V-V
61.5
LOS
4-14.31
CI
1.5
-
2.68
FI
0.79
74.8
2.4
NLOS
4-14.31
CI
3
-
6.4
FI
0.79
99
3.2
NLOS-Best
4-14.31
CI
2.54
-
4.2
FI
0.33
89
1.8
SL FSS Wallpaper
without Humans
V-V
61.5
LOS
4-14.31
CI
1.46
-
2.2
FI
0.76
74
2
NLOS
4-14.31
CI
2.9
-
6.13
FI
-0.16
98
2.6
NLOS-Best
4-14.31
CI
2.5
-
4.2
FI
0.21
90.5
1.2
Humans without SL
FSS Wallpaper
V-V
61.5
LOS
4-14.31
CI
1.76
-
3
FI
1
75.37
2.74
NLOS
4-14.31
CI
3.39
-
7.22
FI
-0.02
101.28
3.87
NLOS-Best
4-14.31
CI
2.9
-
5.87
FI
0.15
95
3.34
Without Humans and
SL FSS Wallpaper
V-V
61.5
LOS
4-14.31
CI
1.7
-
2
FI
1.36
74
2
NLOS
4-14.31
CI
3.4
-
6.88
FI
0.01
98
3.5
NLOS-Best
4-14.31
CI
3
-
5.6
FI
-0.01
90.5
2.24
The FI model indicates lower attenuation as a function of log-distance in some cases (human
without ring FSS wallpaper LOS =1, compared to =1.76, and NLOS =-0.02, compared to =3.39).
However, the FI model parameters can exhibit strange, non-physics-based values, specifically, when is
negative, which implies ultra-low loss with distance (less than in a waveguide), which does not follow basic
physics. We use =1 m in mm-wave PLMs since base stations will be shorter or mounted indoors and closer
to obstructions [23]. The physically-based 1 m FSPL anchor of the CI model for single-frequencies allows
for a simpler model (only one parameter) with virtually no decrease in model accuracy by representing free-
space propagation close to the transmitting antenna. Therefore, the more physically sound and simpler CI
model with a 1 m free space-reference distance term is more convenient to use to model indoor mm-wave
channels. Figure 25 shows scatter plots for CI PLM parameters inside modified indoor environments for
different scenarios as shown in: Figure 25(a) for SL FSS wallpaper with humans, Figure 25(b) for SL FSS
wallpaper without humans, Figure 25(c) for humans without SL FSS wallpaper, and Figure 25(d) for a
scenario without humans and SL FSS wallpaper, for co-polarized antennas at Tx, 20 LOS, and 122 NLOS
readings.
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(a)
(b)
(c)
(d)
Figure 25. Single-frequency (61.5 GHz) CI (= 1 m) PLM parameters scatter plot for Tx at a height of
2.5 m, and Rx antennas height of 1.5 m in an atypical modified indoor office environment for co-polarized
antennas: (a) SL FSS wallpaper with humans, (b) SL FSS wallpaper without humans, (c) humans without
SL FSS wallpaper, and (d) without humans and SL FSS wallpaper
4. CONCLUSION
In order to enhance the performance of indoor 60 GHz wireless networks as a case study multiple
input multiple output (MIMO) system, SL FSS has been selected because the propagation of 60 GHz can be
easily blocked by obstacles or humans. Results showed that received signal power had been enhanced by an
average of 6.87 dB for MIMO system. However, the presence of human bodies attenuated the strength of the
received signal power by an average of 2.5 dB, and decreased the capacity of system. While using SL FSS
wallpaper, the capacity for MIMO system generally will be enhanced, which proved that the presence of
SL FSS wallpaper in an indoor environment increased the strong reflected wave components in each Rx
location.
This paper also described mm-wave propagation simulations in modified indoor scenarios at
61.5 GHz and presented and compared the single-frequency FI and CI PLMs. Single-frequency path loss
results showed that the CI model is preferable to the FI model (presently used in 3GPP) for modified indoor
environments due to its physical basis, simplicity, and robustness over measured frequencies and distance
ranges. The CI model is physically tied to the TX power using a close-in free space reference and
standardized measurements around an inherent 1 m free space reference distance that is physically based.
Thus, it is easy to use for varying distances since it involves the use of a single parameter (PLE, or ).
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Int J Elec & Comp Eng, Vol. 14, No. 3, June 2024: 2737-2752
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BIOGRAPHIES OF AUTHORS
Nidal Qasem received his B.Sc. degree in electronics and communications
engineering (Honours) from Al-Ahliyya Amman University, Amman, Jordan, in 2004. He
obtained his M.Sc. degree in digital communication systems for networks and mobile
applications (DSC) in 2006, followed by a Ph.D. in wireless and digital communication
systems, both from Loughborough University, Loughborough, United Kingdom. He currently
holds the position of full professor in the Department of Communications and Computer
Engineering at Al-Ahliyya Amman University. His research interests include propagation
control in buildings, specifically improving the received power, FSS measurements and
designs, antennas, ultra-wide band, orbital angular momentum, and wireless system
performance analyses. He is a senior member of the IEEE. He can be contacted at email:
Ne.qasem@ammanu.edu.jo.
Mohammad Alkhawatrah received the B.S. and M.S. degrees in communication
engineering from Al-Ahliyya Amman University (AAU), Amman, Jordan, in 2008 and 2016,
respectively. He received the Ph.D. degree from the Signal Processing and Networks Research
Group in 2020 from Wolfson School of Mechanical, Electrical and Manufacturing
Engineering at Loughborough University, Loughborough, U.K. He is currently an assistance
professor in electronic and communication department in Al-Ahliyya Amman University. His
research interests include buffer-aided relays, non-orthogonal multiple access, relay selection,
machine learning, AI, cooperative networks and signal processing. He can be contacted at
email: M.alkhawatrah@ammanu.edu.jo.
