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Citation: Oleiwi, H.W.; Saeed, N.;
Al-Raweshidy, H. Cooperative
SWIPT MIMO-NOMA for Reliable
THz 6G Communications. Network
2022,2, 257–269. https://doi.org/
10.3390/network2020017
Academic Editor: Christos Bouras
Received: 12 March 2022
Accepted: 22 April 2022
Published: 24 April 2022
Publisher’s Note: MDPI stays neutral
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Copyright: © 2022 by the authors.
Licensee MDPI, Basel, Switzerland.
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distributed under the terms and
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Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
Article
Cooperative SWIPT MIMO-NOMA for Reliable THz 6G
Communications
Haider W. Oleiwi 1,* , Nagham Saeed 2and Hamed Al-Raweshidy 1
1Department of Electronic and Electrical Engineering, Brunel University London, London UB8 3PH, UK;
hamed.al-raweshidy@brunel.ac.uk
2School of Computing and Engineering, University of West London, London W5 5RF, UK;
nagham.saeed@uwl.ac.uk
*Correspondence: haider.al-lami@brunel.ac.uk
Abstract:
In this paper, cooperative simultaneous wireless information and power transfer (SWIPT)
terahertz (THz) multiple-input multiple-output (MIMO) nonorthogonal multiple access (NOMA) are
considered. The aim is to improve wireless connectivity, resource management, scalability, and user
fairness, as well as to enhance the overall performance of wireless communications and reliability.
We optimized the current wireless communication systems by utilizing MIMO-NOMA technology
and THz frequencies, exploring the performance and gains obtained. Hence, we developed a path-
selection mechanism for the far user to enhance the system performance. The EH SWIPT approach
used to improve THz communications performance was investigated. Moreover, we proposed a
reliable transmission mechanism with a non-LoS (NLoS) line of THz communications for open areas
or any location where the intelligent reflecting surface (IRS) cannot be deployed, in addition to
using the cheap decode-forward (DF) relaying instead of IRS. The performance and scalability of
the upgradeable system were examined, using adjustable parameters and the simplest modulation
scheme. The system presents a noticeable improvement in energy efficiency (EE) and spectral
efficiency (SE), in addition to reliability. Accordingly, the outcome showed an improvement in
the overall reliability, SE, EE, and outage probability as compared to the conventional cooperative
networks of the recent related work (e.g., cooperative MIMO-NOMA with THz) by multiple times
with a simpler design, whereas it outperformed our previous work, i.e., cooperative SWIPT SISO-
NOMA with THz, by more than 50%, with a doubled individual user gain. This system reduces the
transceiver hardware and improves reliability with increasing transmission rates.
Keywords:
cooperative networks; energy efficiency; energy harvesting; MIMO-NOMA path selection;
outage probability; reliable THz communications; resource management; spectral efficiency
1. Introduction
The wireless communication field has witnessed a rapid rise with a significant expan-
sion of smart gadgets, new technologies, and modern applications. The critical requirement
for fast data transport combined with the global ubiquity of services has resulted in ground-
breaking research. Energy efficiency (EE) and spectral efficiency (SE) are two distinct
metrics that assess system performance [
1
–
4
]. It is critically required to enhance EE and SE
to fulfill the strict requirements of diverse emerging applications, adapting to the upgrades
of the next era and eliminating power consumption of the required equipment [
5
–
10
]. The
efficient use of energy has become an inevitable demand in the next generation of 6G to
support its practicability and satisfy its needs [
11
]. Terahertz (THz) communication [
12
]
will have a significant impact on future generations. According to Shannon’s equation,
SE is determined on the basis of bandwidth (BW) availability. THz represents the un-
explored electromagnetic (EM) gap (0.1–10) THz between EM and optical bands; it has
piqued the interest of the research community toward 6G because of its favored benefits.
THz is regarded as an essential pier for 6G due to its capacity and capabilities to build an
Network 2022,2, 257–269. https://doi.org/10.3390/network2020017 https://www.mdpi.com/journal/network
Network 2022,2258
adequate system, supporting a wide range of applications due to its very short wavelength
(
λ
) of
3000–30 µm
and other features, e.g., very high frequencies, ultrawide BW, very high
data rates, enormous throughput, very low latency, and excellent directivity. THz has
encouraged researchers to investigate its capabilities to enable THz communications as it
outperforms the two adjacent frequency bands in some ways. THz transmitters/receivers
are expected to be manufactured using electronic, photonic, and plasmonic technologies.
It is expected to be integrated with optical networks, providing alternate signals for op-
tical pathways in various cases, e.g., backhaul–backhaul, kiosk–node, data center, and
intra-device interconnections [
13
]. As a result, IEEE Std. 802.15.3d–2017 specifies the
disadvantages of visible water vapor absorption and path losses, dividing the THz gap
across many sub-windows. However, these windows are being thoroughly investigated in
order to accommodate 6G services, with certain exceptions in which some 6G services will
be incompatible with THz bands [
14
]. The need for fully connected systems has arisen as
a result of Internet of everything (IoE) requirements. There are restrictions to 5G systems
that prevent any additions or enhancements to satisfy these needs [15–18].
We aimed to improve wireless connectivity, resource management, scalability, and user
fairness, as well as to enhance the overall performance of 6G wireless communications and
reliability. Hence, we optimized the current wireless communication systems by utilizing
MIMO-NOMA technology and THz frequencies, exploring the performance and gains
obtained. The main contributions of this paper are as follows:
(1)
We propose a reliable transmission with a non-LOS (NLoS) line of THz communi-
cations to overcome THz coverage shortage for open areas or any location where
IRS cannot be deployed, in addition to using a simplified cost-effective DF relaying
instead of IRS.
(2)
We design a system with low power consumption, complexity, and cost by inte-
grating THz, NOMA, MIMO, cooperative networking, and EH (SWIPT) techniques,
improving SE, EE, and other metrics compared to the state of the art.
(3)
We develop a path-selection mechanism for the potential NOMA-based far users to
enhance the system performance and reliability.
(4)
Given the flexible structure, we recommend exploiting an existing user in the cell for
relaying and not dedicating a fixed device, achieving a synergic coexistence with the
expected mobile 6G infrastructure.
(5)
To enhance the SIC procedure, we suggest two-user clustering to prevent propagat-
ing errors, complications, and spectral deficiencies due to the burden of the addi-
tional operations.
(6)
We manage the performance and scalability of the spectral and energy efficient up-
gradeable system, using adjustable parameters and the simplest modulation scheme;
hence, this system can be upgraded on the basis of the planner’s preferences.
The remainder of this paper is organized as follows: Section 2gives a brief background
of the mechanisms used in this paper; Section 3describes a number of related studies
and the discussed outcomes; Section 4describes the proposed model and presents the
derivation of mathematical closed forms, describing the advantages of the proposed system
and the adopted techniques for next generations to achieve the targeted goals; Section 5
describes the system implementation; Section 6presents the mathematical analysis and
simulations, where we model the proposed system by discussing the results and how they
bring value to existing systems. The idea behind using the DF relaying user instead of
the preceding systems is demonstrated in a discussion centered on enhancing the system
performance of THz-NOMA systems, managing the resources; Section 7summarizes the
conclusions of the study.
2. Background
To develop a communication system that meets the extreme values of the emerging
requirements in terms of connectivity, SE, latency, data rate, reliability, and user fairness,
enabling new applications, EE, and cost-effectiveness, it is necessary to merge some of the
Network 2022,2259
key enabling techniques to achieve the required objectives. As a result, nonorthogonal
multiple access in the power domain (NOMA) [
19
] is the most well-known nominee for
developing 6G systems, exceeding the performance of traditional orthogonal multiple
access (OMA) schemes. Multiple-input multiple-output (MIMO)-NOMA is the focus of our
study. The NOMA mechanism superimposes multiple signals at the transmitter (Tx), and
then filters them at the receiver (Rx) by successive interference cancelation (SIC) procedures,
thereby increasing channel capacity primarily determined by BW. The interference and
noise, on the other hand, are removed by the SIC at the Rx. NOMA multiplexing is achieved
by allocating different power coefficients to users on the basis of their channel conditions.
At Tx, all users’ signals are overlaid. The application of SIC at Rx is used to demultiplex
NOMA signals. Because the line of sight (LoS) is the primary transmission path, grouping
or clustering of the serviced users is critical for improving SE and reducing the complexity
of NOMA-based THz transmission. MIMO-based NOMA BS/users depend basically on
channel state information (CSI) (or other metrics often) for successful SIC decoding at the
Rx. With a large number of users, user clustering may be difficult; consequently, we strive
to design low-complexed systems to solve clustering complications [
20
,
21
]. Hence, not only
is SIC operation CSI-related, but it can also be quality service-related or hybrid-related [
20
].
However, all modulation systems have a significant barrier to CSI acquisition at the Tx
and Rx [
14
]. As a result, we employ binary phase-shift keying (BPSK) in the proposed
system, which has several advantages over other formats. To address the challenges
of THz communications, researchers are looking into all options, highlighting NOMA-
assisted cooperative networks. Cooperative networking provides a number of benefits,
including increased reliability and capacity, as well as a larger coverage area, all of which
improve overall performance, i.e., implementing energy harvesting (EH) with cooperative
NOMA [
22
], which is the focus of the proposed article of THz communications. While
applying NOMA to the proposed system, decode-forward (DF) relaying is adopted instead
of the complex and costly intelligent reflecting surface (IRS). In NOMA, the far users’
signal is already contained in the superposed signal; therefore, that copy can be utilized
for relaying. That is preferable to utilizing an additional relaying device with additional
complexity and power consumption. While THz-NOMA requires heavy computational SIC
operations at the Rx, employing cooperative networking continually drains the relaying
user’s battery, resulting in system failure. As a result, research activities are aimed at
overcoming that issue, transforming into green communications [
23
] by applying the EH
technique. Radiofrequency (RF) power, which exists everywhere surrounding almost all
user equipment (UE), is used to send energy and information to distant destinations. Using
basic RF circuits, EH allows UEs to harvest that energy. We can then use that gathered
power in the broadcasts to convey signals without putting additional strain on the relaying
user’s battery. Through EH power splitting, the relaying user splits the power it receives
into harvesting and decoding fractions, operating them at the same time, resulting in
the principle of simultaneous wireless information and power transfer (SWIPT). SWIPT
enables the relaying user to capture power from the transmitted signal and use it for data
retransmission to a farther user, as depicted in Figure 1. Ultimately, the entire capacity and
outage probability (OP) are significantly improved.
Network 2022,2260
Network 2022, 2, FOR PEER REVIEW 5
Figure 1. SWIPT with cooperative NOMA.
3. Related Works
Cooperative networking has been previously investigated utilizing a variety of cases
and situations; the major benefits were clearly demonstrated while the drawbacks of
adopting this strategy were addressed. Other technologies of this study, i.e., EH, NOMA,
and THz, were discussed separately or in combination to attain a specific influence on the
field. The drawbacks of employing those technologies were thoroughly explored,
including the flaws, restrictions, and lack of performance. In [23,24], despite the
consideration of the IRS as an edge of technology to improve source to destination
transmission in particular cases of interrupted communication path, it must outperform
the usage of relaying regarding complexity, energy, and cost, as shown in Figure 2. Briefly,
when comparing IRS to the older DF relay, the general impression of this work stated that
a supreme data rate is necessary to outperform the DF relay regarding transmit power
minimization and EE maximization. Furthermore, IRS requires additional hardware.
Figure 2. Relay-based transmission strategy.
Tataria et al. [14] discussed the difficulties in designing and deploying IRS to support
6G communication networks, i.e., aligning transmission beams for time-based steering,
interference management, and EE degradation. The obstacles that IRS implementation
faces include further required procedures, such as the impact of physical coverage area,
equipment, system components, and additional maintenance/cost for wireless
communications when deploying IRS. Atmospheric effects cause aggregate or
proportional failures. IRS uniformity system implementation and interactivity with radio
traffic are required for efficient signaling. However, the additional steps will complicate
and exhaust network resources. Thus, despite using the promising IRS technology, the
proposed system still faces difficulties and noticeable drawbacks.
In [25], clustered, pre-coded, and power-allocated systems were all investigated.
They developed an AI-based algorithm to present a clustering technique for THz MIMO-
NOMA designs. This methodology comes at the cost of the required running time of the
huge dataset, as well as the updated dataset acquisition needed. On the other hand, in
Figure 1. SWIPT with cooperative NOMA.
3. Related Works
Cooperative networking has been previously investigated utilizing a variety of cases
and situations; the major benefits were clearly demonstrated while the drawbacks of
adopting this strategy were addressed. Other technologies of this study, i.e., EH, NOMA,
and THz, were discussed separately or in combination to attain a specific influence on the
field. The drawbacks of employing those technologies were thoroughly explored, including
the flaws, restrictions, and lack of performance. In [
23
,
24
], despite the consideration
of the IRS as an edge of technology to improve source to destination transmission in
particular cases of interrupted communication path, it must outperform the usage of
relaying regarding complexity, energy, and cost, as shown in Figure 2. Briefly, when
comparing IRS to the older DF relay, the general impression of this work stated that a
supreme data rate is necessary to outperform the DF relay regarding transmit power
minimization and EE maximization. Furthermore, IRS requires additional hardware.
Network 2022, 2, FOR PEER REVIEW 5
Figure 1. SWIPT with cooperative NOMA.
3. Related Works
Cooperative networking has been previously investigated utilizing a variety of cases
and situations; the major benefits were clearly demonstrated while the drawbacks of
adopting this strategy were addressed. Other technologies of this study, i.e., EH, NOMA,
and THz, were discussed separately or in combination to attain a specific influence on the
field. The drawbacks of employing those technologies were thoroughly explored,
including the flaws, restrictions, and lack of performance. In [23,24], despite the
consideration of the IRS as an edge of technology to improve source to destination
transmission in particular cases of interrupted communication path, it must outperform
the usage of relaying regarding complexity, energy, and cost, as shown in Figure 2. Briefly,
when comparing IRS to the older DF relay, the general impression of this work stated that
a supreme data rate is necessary to outperform the DF relay regarding transmit power
minimization and EE maximization. Furthermore, IRS requires additional hardware.
Figure 2. Relay-based transmission strategy.
Tataria et al. [14] discussed the difficulties in designing and deploying IRS to support
6G communication networks, i.e., aligning transmission beams for time-based steering,
interference management, and EE degradation. The obstacles that IRS implementation
faces include further required procedures, such as the impact of physical coverage area,
equipment, system components, and additional maintenance/cost for wireless
communications when deploying IRS. Atmospheric effects cause aggregate or
proportional failures. IRS uniformity system implementation and interactivity with radio
traffic are required for efficient signaling. However, the additional steps will complicate
and exhaust network resources. Thus, despite using the promising IRS technology, the
proposed system still faces difficulties and noticeable drawbacks.
In [25], clustered, pre-coded, and power-allocated systems were all investigated.
They developed an AI-based algorithm to present a clustering technique for THz MIMO-
NOMA designs. This methodology comes at the cost of the required running time of the
huge dataset, as well as the updated dataset acquisition needed. On the other hand, in
Figure 2. Relay-based transmission strategy.
Tataria et al. [
14
] discussed the difficulties in designing and deploying IRS to support
6G communication networks, i.e., aligning transmission beams for time-based steering,
interference management, and EE degradation. The obstacles that IRS implementation
faces include further required procedures, such as the impact of physical coverage area,
equipment, system components, and additional maintenance/cost for wireless communica-
tions when deploying IRS. Atmospheric effects cause aggregate or proportional failures.
IRS uniformity system implementation and interactivity with radio traffic are required for
efficient signaling. However, the additional steps will complicate and exhaust network
resources. Thus, despite using the promising IRS technology, the proposed system still
faces difficulties and noticeable drawbacks.
In [
25
], clustered, pre-coded, and power-allocated systems were all investigated. They
developed an AI-based algorithm to present a clustering technique for THz MIMO-NOMA
designs. This methodology comes at the cost of the required running time of the huge
dataset, as well as the updated dataset acquisition needed. On the other hand, in [
26
],
Network 2022,2261
a widely used spatially multiplexed was presented, while sub-THz was investigated to
produce very high data rates and spectral efficiency. For data rate maximization, an inves-
tigation [
27
] was conducted for the power allocating issue in NOMA-based cooperative
MIMO in HD and FD THz communications, which is still insufficient compared to the
assumed targets of the proposed system in this paper.
Oleiwi and Al-Raweshidy studied in their recent work [
28
] the contribution of EH and
other key enabling technologies to enhance system performance, considering a relatively
similar concept with a simplified system of single-input single-output (SISO) scheme equip-
ment. However, our previous papers [
29
,
30
] investigated the impact of the multihoming
principle on improving system reliability, operational efficiency, and the overall perfor-
mance. The value of multihoming management was addressed to keep communication
going for the multihomed user, in addition to presenting an interface selectivity technique.
4. System Model Design
Recent academic and industrial research stated the assumption of deploying ultra-
dense heterogeneous networks (UDHNs), with a large number of distributed base stations,
access points, relays, and repeaters to the expected 6G densified infrastructure. The pre-
sented simple system in Figure 3is suggested to solve the problems of the THz commu-
nications’ lack of a coverage area, connection failures, and SIC complexity. Particular use
cases are studied, e.g., rural areas, countryside, or any other place where IRS and other
supporting equipment cannot be deployed, providing dynamic path selectivity in the case
of the user’s link failure. The system considers a small cell with MIMO-NOMA-based
downlink transmission and two SWIPT-paired clustered users. The BS sends the super-
imposed signal simultaneously to both NOMA served users, the near user (NU) and the
distant user (FU). At a certain moment, the BS to FU path is blocked by an obstruction,
resulting in significant shadowing. As a result, the FU is unable to identify its obstructed
signal. The NU, on the other hand, establishes a strong connection with the BS. According
to NOMA principles, the NU is supposed to first decode the FU’s signal before removing
it by the SIC process, and then decode its intended signal. Hence, NU receives a copy of
the FU’s data, such that FU can rely on NU to connect to the BS by exploiting it as a DF
relay. For relaying, the energy in the NU’s battery is insufficient to convey the data to the
FU. To this end, we recommended that NU makes use of EH’s power-splitting protocol
(SWIPT) to harvest energy from the surrounding RF energy to use it for this retransmission
(relaying process). The transmission procedure is divided into two parts. The NU receives
the BS superposed signal at the first phase, whereas the power-splitting procedure captures
a portion of the NU’s harvested power; however, the remaining power is used for data
decoding. The captured energy is then used by NU to convey the FU’s information to FU
in the second phase.
Network 2022, 2, FOR PEER REVIEW 6
[26], a widely used spatially multiplexed was presented, while sub-THz was investigated
to produce very high data rates and spectral efficiency. For data rate maximization, an
investigation [27] was conducted for the power allocating issue in NOMA-based
cooperative MIMO in HD and FD THz communications, which is still insufficient
compared to the assumed targets of the proposed system in this paper.
Oleiwi and Al-Raweshidy studied in their recent work [28] the contribution of EH
and other key enabling technologies to enhance system performance, considering a
relatively similar concept with a simplified system of single-input single-output (SISO)
scheme equipment. However, our previous papers [29,30] investigated the impact of the
multihoming principle on improving system reliability, operational efficiency, and the
overall performance. The value of multihoming management was addressed to keep
communication going for the multihomed user, in addition to presenting an interface
selectivity technique.
4. System Model Design
Recent academic and industrial research stated the assumption of deploying ultra-
dense heterogeneous networks (UDHNs), with a large number of distributed base
stations, access points, relays, and repeaters to the expected 6G densified infrastructure.
The presented simple system in Figure 3 is suggested to solve the problems of the THz
communications’ lack of a coverage area, connection failures, and SIC complexity.
Particular use cases are studied, e.g., rural areas, countryside, or any other place where
IRS and other supporting equipment cannot be deployed, providing dynamic path
selectivity in the case of the user’s link failure. The system considers a small cell with
MIMO-NOMA-based downlink transmission and two SWIPT-paired clustered users. The
BS sends the superimposed signal simultaneously to both NOMA served users, the near
user (NU) and the distant user (FU). At a certain moment, the BS to FU path is blocked by
an obstruction, resulting in significant shadowing. As a result, the FU is unable to identify
its obstructed signal. The NU, on the other hand, establishes a strong connection with the
BS. According to NOMA principles, the NU is supposed to first decode the FU’s signal
before removing it by the SIC process, and then decode its intended signal. Hence, NU
receives a copy of the FU’s data, such that FU can rely on NU to connect to the BS by
exploiting it as a DF relay. For relaying, the energy in the NU’s battery is insufficient to
convey the data to the FU. To this end, we recommended that NU makes use of EH’s
power-splitting protocol (SWIPT) to harvest energy from the surrounding RF energy to
use it for this retransmission (relaying process). The transmission procedure is divided
into two parts. The NU receives the BS superposed signal at the first phase, whereas the
power-splitting procedure captures a portion of the NU’s harvested power; however, the
remaining power is used for data decoding. The captured energy is then used by NU to
convey the FU’s information to FU in the second phase.
Figure 3. Cooperative SWIPT MIMO-NOMA in THz model.
A Rayleigh fading channel with mean = 0 and variance =
Transmission Distance-THz total losses was conducted in this analysis for all cases. We set
Figure 3. Cooperative SWIPT MIMO-NOMA in THz model.
A Rayleigh fading channel with mean = 0 and variance =
Transmission Distance−THz total losses
was conducted in this analysis for all cases. We set additive white gaussian noise (AWGN)
Network 2022,2262
with mean = 0 and variance of
σ2
, representing the added noise. The probability density
function (PDF) for the point z is given by
f(z;σ)=1
√2πσ2exp−z2
2σ2. (1)
As space attenuation and molecule absorption are considered in the cooperative SWIPT
NOMA signal, the path loss of the NLoS link is greater than that of the LoS link. If the LoS
link prevails, then the NLoS impact can be ignored [
22
]. In free space, the
THz total loss
(
η
)
is set as extraordinarily large. For the users k, the channel gain is written as
hk=√As1
ηG, (2)
where Adenotes the MIMO antennas, Gdenotes the gain of the antenna, and
η
represents
the source–destination THz total losses, written as
η= ( 4πf d
C)
2
ea(f)d, (3)
where
f
denotes the THz,
d
denotes the source–destination distance,
a(f)
represents the
absorbing coefficient, and Cdenotes the velocity of light.
According to the proposed case, the closed-form derivations are presented below.
Stage 1, BS to NU transmission:
The BS superimposed signal is
X=√P√αn xn +pαf x f , (4)
where P denotes the transmit power,
α
nand
α
fdenote the NU and FU powers, respectively,
and
xn
and
x f
denote the NU and FU signals, respectively. However, FU cannot detect its
signal due to obstruction. The NU signal is given by
yn =√P√αn xn +pαf x f hsn+wn, (5)
hsn=(h11 +h12), (6)
yn =√P√αn xn +pαf x f (h11 +h12)+wn, (7)
where
hsn(h11 +h12)
is base station to the near user (BS-NU) Rayleigh fading coefficient
with mean = 0 and variance of
dsn−η
, dsn denotes the BS-NU distance, and wn is the
AWGN with mean = 0 and variance of
σ2
. Using yn, NU captures a portion of energy
named the EH coefficient (
ψ
). The remaining energy portion (1
−ψ
) is allocated to data
decoding. With EH, the data decoded signal is expressed as
yD =p(1−ψ)yn +weh
=p(1−ψ)√P√αn xn +pαf x f +p(1−ψ)wn
+weh,
(8)
where weh denotes thermal noise (zero mean and variance of
σ2
). For the mathematical
process, we abandon the wn harvested energy; consequently, yD is given by
yD =q(1−ψ)√P√αn xn +pαf x f +weh. (9)
Network 2022,2263
As a function of yD, NU decodes
x f
straightaway. The NU rate to decode FU’s data is
calculated as
Rn f =1
2log2 1+(1−ψ)Pαf|h11 +h12|2
(1−ψ)Pαn|h11 +h12|2+σ2!. (10)
With SIC, the NU rate of NU information decoding is calculated as
Rn f =1
2log2 1+(1−ψ)Pαn|h11 +h12|2
σ2!, (11)
where ψis the captured EH coefficient during the first phase. EH is calculated as
PH =P|h11 +h12|2ζψ, (12)
where ζdenotes the circuitry EH efficiency.
Stage 2, NU to FU DF-relaying:
Using the gathered energy, NU conveys the data to FU (PH). As a result, the NU’s sent
signal is √PH f
x f . (13)
The detected signal at FU is given by
√PH f
x f hn f +w f , (14)
h f =min{(h21 +h22),hn f }, (15)
where hf denotes the minimal Rayleigh fading channel of the selected path between the BS
and FU
(i.e., (h21 +h22)or hn f )
, and hnf is the NU-to-FU Rayleigh channel. The rate of
the FU is represented as
R f =1
2log2 1+PH|h f |2
σ2!. (16)
In the first stage, NU is supposed to decode the FU’s information in order to determine
the ideal power-splitting coefficient, allowing it to properly retransmit FU’s data. To do so,
the constraint Rnf >Rf ∗was set.
The FU target rate is Rf
∗
. This criterion implies that the NU rate for decoding FU data
must be higher than the FU intended rate. To derive
ψ
,
Rn f
in Equation (11) is substituted
into the assumed constraint presented above.
1
2log2 1+(1−ψ)Pαf|h f |2
(1−ψ)Pαn|h f |2+σ2!>R f ∗. (17)
log2 1+(1−ψ)Pαf|h f |2
(1−ψ)Pαn|h f |2+σ2!>2R f ∗. (18)
(1−ψ)Pαf|h f |2
(1−ψ)Pαn|h f |2+σ2
>22R f ∗−1. (19)
The term 22Rf∗−1 is represented by τfto denote the FU targeted SINR.
(1−ψ)Pαf|h f |2
(1−ψ)Pαn|h f |2+σ2
>τf. (20)
(1−ψ)Pαf|h f |2>τf(1−ψ)Pαn|h f |2+τfσ2. (21)
(1−ψ)Pαf|h f |2−τf(1−ψ)Pαn|h f |2>τfσ2. (22)
Network 2022,2264
(1−ψ)P|h f |2(αf−τfαn>τfσ2. (23)
ψ<1−τfσ2
P|h f |2(αf−τfαn. (24)
To guarantee a smaller value of ψ, the above equation can be reshaped as
ψ=1−τfσ2
P|h f |2(αf−τfαn−δ, (25)
where
δ
is represented by a very small value (i.e., 10
−6
); then,
ψ
guarantees the needed
energy to decode the data, achieving the FU targeted rate.
Outage Probability:
It is every user’s chance that the data rate will drop beneath the target. Rn
∗
and Rf
∗
(bits/s/Hz) are the NU and FU targeted rates, respectively.
FU is considered to fail whenever Rf in Equation (16) is smaller than targeted rate,
represented as
PNU =Pr(R f <R f ∗). (26)
The NU must accurately decode both signals: the FU signal and its signal. The NU
and FU targeted rates must be equal to the NU rate. When using SIC, if the NU or FU
targeted rates in Equations (11) and (16) are not sufficient, NU experiences an outage, which
is represented by
PNU =Pr(RNF <Rf ∗)+Pr(RNF >Rf ∗,Rn <Rn∗). (27)
We follow up on the first mode described in the PHY section of [
31
] of the THz single
carrier frequency. This idea is recommended for high-speed transmission links aimed at
bandwidth-based cases, e.g., links of backhaul/backhaul, fronthaul/backhaul, and between
data center racks [
32
]. Due to atmosphere and impact, the accessible spectrum is divided
into multiple channels on the basis of the spectral windows of THz frequencies (from 252.72
to 321.84) GHz, with each channel having its own features [
32
]. There are multiple cases of
2.16 GHz within the THz spectrum, whereby six channels and eight bands (from 2.16 to
69 GHz) are discovered. According to some criteria and constraints, these spectral windows
can be determined.
Despite the variety of available modulation types in THz-SC PHY (BPSK and QPSK
are required), we utilize BPSK as the simplest scheme among the different supported
modulations. Transmission distance and system performance are the critical measures
that must be balanced on the basis of system metrics, considering a range-to-rate tradeoff
strategy [28].
5. Implementation
The first implementation is to show that our simulation is valid when compared to
the mathematical analysis. The simulation described below compares the recent similar
system equipped with the SISO scheme as a baseline to this paper’s scenario of cooperative
SWIPT THz MIMO-NOMA, utilizing moderated parameter settings for transmit frequency,
allocated BW, transmit power, and transmit distance.
(1)
Transmit power, frequency, distance, and BW can be adjusted.
(2)
Targeted rates are 1 Gbps for the FU and 3 Gbps for the NU.
(3)
A power of
−
30 to 30 dBm is dedicated to cover a wider area if the FU goes farther.
Hence, transmit power can be reduced.
(4)
We set a relatively high path-loss exponent
η
= 4; hence, it can be reduced. The
absorption coefficient can be found in [
27
]. The simulations were implemented using
MATLAB(r).
Network 2022,2265
6. Simulation Results
This section includes the implementation of simulations and numerical analysis to
verify the validation of data rates and OP. The simulation findings confirm the obtained
closed forms of the optimized model, and they are compared to earlier research. By existing
an obstruction in the link to the BS, the presented mechanism should allow the obstructed
user to maintain continuous communication. The sections below explain how the pro-
posed system and mechanism can enhance EE, SE, reliability, and system performance by
addressing the distance-limited communications of THz frequencies. Table 1shows the
simulation parameters.
Table 1. Simulation parameters.
Notation Parameters Value
f Frequency 311.04 GHz
BW Bandwidth 12.96 GHz
P Transmission power 30 dBm
dTransmission distance Phase 1 = 20 m
Phase 2 = 30 m
αn NU power coefficient 0.25 of total power
αf FU power coefficient 0.75 of total power
G Antenna gain 25 dB
eta Path loss exponent 4
Target data rate 3, 1 Gbps for NU, FU
6.1. System Validity Analysis
In contrast, a mathematical analysis and simulation were carried out to compare
the system sum throughput and OP, using a transmission power of 20 dBm for system
validation, verifying the intended objectives.
Figures 4and 5exhibit the striking match between the mathematical analysis of the
derived close forms and simulation results. They confirm the analysis accuracy and system
validity, now including the uniqueness of new values. We thoroughly study system metrics
throughout the remaining parts of this paper.
Sum Throughput Versus Transmit Power:
Network 2022, 2, FOR PEER REVIEW 10
6. Simulation Results
This section includes the implementation of simulations and numerical analysis to
verify the validation of data rates and OP. The simulation findings confirm the obtained
closed forms of the optimized model, and they are compared to earlier research. By
existing an obstruction in the link to the BS, the presented mechanism should allow the
obstructed user to maintain continuous communication. The sections below explain how
the proposed system and mechanism can enhance EE, SE, reliability, and system
performance by addressing the distance-limited communications of THz frequencies.
Table 1 shows the simulation parameters.
Table 1. Simulation parameters.
Notation Parameters Value
f Frequency 311.04 GHz
BW Bandwidth 12.96 GHz
P Transmission power 30 dBm
d Transmission distance Phase 1 = 20 m
Phase 2 = 30 m
αn NU power coefficient 0.25 of total power
αf FU power coefficient 0.75 of total power
G Antenna gain 25 dB
eta Path loss exponent 4
Target data rate 3, 1 Gbps for NU, FU
6.1. System Validity Analysis
In contrast, a mathematical analysis and simulation were carried out to compare the
system sum throughput and OP, using a transmission power of 20 dBm for system
validation, verifying the intended objectives.
Figure 4 and Figure 5 exhibit the striking match between the mathematical analysis
of the derived close forms and simulation results. They confirm the analysis accuracy and
system validity, now including the uniqueness of new values. We thoroughly study
system metrics throughout the remaining parts of this paper.
Sum Throughput Versus Transmit Power:
Figure 4. Throughput vs. transmit power.
Users’ OP versus Transmit Power:
Figure 4. Throughput vs. transmit power.
Users’ OP versus Transmit Power:
Network 2022,2266
Network 2022, 2, FOR PEER REVIEW 11
Figure 5. OP vs. Transmit Power.
6.2. System Simulation
First, the performance of the system’s served users was individually implemented,
and then we examined the entire system’s sum rate. The performance was compared with
our previous similar SISO-based system model (as a baseline) to explain how the
presented system provides a remarkable improvement of the current wireless
communication systems, by employing the edge of technologies mentioned in this paper.
6.2.1. Achievable Users’ Rates versus Transmit Power
Figure 6 demonstrates the system users’ performance versus the dedicated power.
For the two users, the MIMO technique provides remarkable leverage to system
performance compared to the SISO scheme. The NU performs much better than the FU,
despite the EH technique allocating the essential energy to achieve the target rate and
harvesting the remainder for retransmission, thus clarifying the impact of comparative
THz losses. However, the FU still achieves a data rate greater than the target despite the
interference it experiences (as the FU does not perform the SIC process). Furthermore, we
can make use of the harvested power for further EH processes.
Figure 6. Rates vs. transmit power.
6.2.2. OP versus Transmit Power
Similarly, for both NOMA users, the MIMO technique provides a notable
enhancement of system performance compared to the SISO scheme, as shown in Figure 7.
In spite of having more dedicated power than the NU, the FU has a higher outage. This
reflects the expected performance given their distinct channel variations.
Figure 5. OP vs. Transmit Power.
6.2. System Simulation
First, the performance of the system’s served users was individually implemented,
and then we examined the entire system’s sum rate. The performance was compared with
our previous similar SISO-based system model (as a baseline) to explain how the presented
system provides a remarkable improvement of the current wireless communication systems,
by employing the edge of technologies mentioned in this paper.
6.2.1. Achievable Users’ Rates versus Transmit Power
Figure 6demonstrates the system users’ performance versus the dedicated power. For
the two users, the MIMO technique provides remarkable leverage to system performance
compared to the SISO scheme. The NU performs much better than the FU, despite the
EH technique allocating the essential energy to achieve the target rate and harvesting
the remainder for retransmission, thus clarifying the impact of comparative THz losses.
However, the FU still achieves a data rate greater than the target despite the interference it
experiences (as the FU does not perform the SIC process). Furthermore, we can make use
of the harvested power for further EH processes.
Network 2022, 2, FOR PEER REVIEW 11
Figure 5. OP vs. Transmit Power.
6.2. System Simulation
First, the performance of the system’s served users was individually implemented,
and then we examined the entire system’s sum rate. The performance was compared with
our previous similar SISO-based system model (as a baseline) to explain how the
presented system provides a remarkable improvement of the current wireless
communication systems, by employing the edge of technologies mentioned in this paper.
6.2.1. Achievable Users’ Rates versus Transmit Power
Figure 6 demonstrates the system users’ performance versus the dedicated power.
For the two users, the MIMO technique provides remarkable leverage to system
performance compared to the SISO scheme. The NU performs much better than the FU,
despite the EH technique allocating the essential energy to achieve the target rate and
harvesting the remainder for retransmission, thus clarifying the impact of comparative
THz losses. However, the FU still achieves a data rate greater than the target despite the
interference it experiences (as the FU does not perform the SIC process). Furthermore, we
can make use of the harvested power for further EH processes.
Figure 6. Rates vs. transmit power.
6.2.2. OP versus Transmit Power
Similarly, for both NOMA users, the MIMO technique provides a notable
enhancement of system performance compared to the SISO scheme, as shown in Figure 7.
In spite of having more dedicated power than the NU, the FU has a higher outage. This
reflects the expected performance given their distinct channel variations.
Figure 6. Rates vs. transmit power.
6.2.2. OP versus Transmit Power
Similarly, for both NOMA users, the MIMO technique provides a notable enhancement
of system performance compared to the SISO scheme, as shown in Figure 7. In spite of
having more dedicated power than the NU, the FU has a higher outage. This reflects the
expected performance given their distinct channel variations.
Network 2022,2267
Network 2022, 2, FOR PEER REVIEW 12
Figure 7. OP vs. transmit power.
6.2.3. Achievable Sum Rates versus Transmit Power
In Figure 8, it is proven that the MIMO technique provides added value through a
remarkable impact on the system performance compared to the SISO scheme. Moreover,
the presented system outperforms the state of the art considering our simpler and cost-
effective model, which has lower complexity and achieves higher EE and SE. Hence, we
achieve the same target for the two users using relatively less power than allocated in
previous research (e.g., [27]). This demonstrates the significance of using the energy-
harvesting technique with the proposed strategy, representing additional gain and a
significant contribution.
Figure 8. Sum rates vs. transmit power.
In contrast, MIMO-NOMA systems might face some drawbacks, e.g., the
computational complications of MIMO and procedural complexity of SIC-dependent
NOMA, as SIC is widely thought to be implemented flawlessly, notwithstanding the
possibility of procedural errors. Thus, it is critical to keep the number of users per cluster
as low as possible, as user CSI acquisition has a significant impact on SIC implementation.
7. Conclusions
This paper thoroughly studied the application of the EH technique to a cooperative
MIMO-NOMA system for THz communications. The EH coefficient was derived to verify
the intended SINR, data rates, and spectral efficiency for MIMO-NOMA served users. The
maximal possible comparable EH-based energy efficiency was examined in accordance
with a 1 Gbps reference point to the far user and 3 Gbps to the near user. The system
outperformed comparable studies (e.g., similar cooperative MIMO-NOMA THz
Figure 7. OP vs. transmit power.
6.2.3. Achievable Sum Rates versus Transmit Power
In Figure 8, it is proven that the MIMO technique provides added value through a
remarkable impact on the system performance compared to the SISO scheme. Moreover, the
presented system outperforms the state of the art considering our simpler and cost-effective
model, which has lower complexity and achieves higher EE and SE. Hence, we achieve the
same target for the two users using relatively less power than allocated in previous research
(e.g., [
27
]). This demonstrates the significance of using the energy-harvesting technique
with the proposed strategy, representing additional gain and a significant contribution.
Network 2022, 2, FOR PEER REVIEW 12
Figure 7. OP vs. transmit power.
6.2.3. Achievable Sum Rates versus Transmit Power
In Figure 8, it is proven that the MIMO technique provides added value through a
remarkable impact on the system performance compared to the SISO scheme. Moreover,
the presented system outperforms the state of the art considering our simpler and cost-
effective model, which has lower complexity and achieves higher EE and SE. Hence, we
achieve the same target for the two users using relatively less power than allocated in
previous research (e.g., [27]). This demonstrates the significance of using the energy-
harvesting technique with the proposed strategy, representing additional gain and a
significant contribution.
Figure 8. Sum rates vs. transmit power.
In contrast, MIMO-NOMA systems might face some drawbacks, e.g., the
computational complications of MIMO and procedural complexity of SIC-dependent
NOMA, as SIC is widely thought to be implemented flawlessly, notwithstanding the
possibility of procedural errors. Thus, it is critical to keep the number of users per cluster
as low as possible, as user CSI acquisition has a significant impact on SIC implementation.
7. Conclusions
This paper thoroughly studied the application of the EH technique to a cooperative
MIMO-NOMA system for THz communications. The EH coefficient was derived to verify
the intended SINR, data rates, and spectral efficiency for MIMO-NOMA served users. The
maximal possible comparable EH-based energy efficiency was examined in accordance
with a 1 Gbps reference point to the far user and 3 Gbps to the near user. The system
outperformed comparable studies (e.g., similar cooperative MIMO-NOMA THz
Figure 8. Sum rates vs. transmit power.
In contrast, MIMO-NOMA systems might face some drawbacks, e.g., the computa-
tional complications of MIMO and procedural complexity of SIC-dependent NOMA, as
SIC is widely thought to be implemented flawlessly, notwithstanding the possibility of
procedural errors. Thus, it is critical to keep the number of users per cluster as low as
possible, as user CSI acquisition has a significant impact on SIC implementation.
7. Conclusions
This paper thoroughly studied the application of the EH technique to a cooperative
MIMO-NOMA system for THz communications. The EH coefficient was derived to verify
the intended SINR, data rates, and spectral efficiency for MIMO-NOMA served users. The
maximal possible comparable EH-based energy efficiency was examined in accordance
with a 1 Gbps reference point to the far user and 3 Gbps to the near user. The system
outperformed comparable studies (e.g., similar cooperative MIMO-NOMA THz communi-
cation system) in terms of gain with a simpler design. Furthermore, it outperformed our
previous work using a similar simplified system with an SISO scheme, providing better
Network 2022,2268
overall performance (in terms of reliability, OP, SE, and EE) by more than 50% (with a
doubled individual user gain), considering the simplicity and reliability tradeoff. Overall,
the findings demonstrated how the defined strategies successfully preserved continued
communication between the BS and the potentially obstructed FU, as well as how the
overall system performance was greatly enhanced. Additionally, this work provided a
dynamic path-selection mechanism for further reliability. Moreover, it is worth noticing
that the scalability of the system presents a flexible adaptation for system planners as the
examined parameters are adjustable according to the deployment situations. To the best of
the authors’ knowledge, SWIPT has never been adopted with such a system of cooperative
THz MIMO-NOMA systems achieving such results. The SE, EE, and reliability have not
previously been improved, especially using the dynamic mechanism we adopted.
Author Contributions:
Conceptualization, H.W.O.; methodology, H.W.O.; software, H.W.O.; vali-
dation, H.W.O.; formal analysis, H.W.O.; investigation, H.W.O.; resources, H.W.O.; data curation,
H.W.O.; writing—original draft preparation, H.W.O.; writing—review and editing, N.S.; visualization,
N.S.; supervision, H.A.-R.; project administration, H.A.-R.; funding acquisition, N.S. All authors have
read and agreed to the published version of the manuscript.
Funding: This research received no external funding.
Conflicts of Interest: The authors declare no conflict of interest.
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