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Sensors 2022, 22, 6200. https://doi.org/10.3390/s22166200 www.mdpi.com/journal/sensors
Article
SWIPT-Pairing Mechanism for Channel-Aware Cooperative
H-NOMA in 6G Terahertz Communications
Haider W. Oleiwi * and Hamed Al-Raweshidy
Department of Electronic and Electrical Engineering, Brunel University, London UB8 3PH, UK
* Correspondence: haider.al-lami@brunel.ac.uk
Abstract: The constraints of 5G communication systems compel further improvements to be com-
patible with 6G candidate technologies, especially to cope with the limited wavelengths of blockage-
sensitive terahertz (THz) frequencies. In this paper integrating cooperative simultaneous wireless
information and power transfer (SWIPT) and hybrid-non-orthogonal multiple access (H-NOMA)
using THz frequency bands are suggested. We investigated and developed an optimal SWIPT-pair-
ing mechanism for the multilateral proposed system that represents a considerable enhancement in
energy/spectral efficiencies while improving the significant system specifications. Given the system
performance investigation and the gains achieved, in this paper, wireless communication systems
were optimized and upgraded, making use of promising technologies including H-NOMA and THz
communications. This process aimed to alleviate the THz transmission challenges and improve
wireless connectivity, resource availability, processing, robustness, capacity, user-fairness, and
overall performance of communication networks. It thoroughly optimized the best H-NOMA pair-
ing scheme for cell users. The conducted results showed how the proposed technique managed to
improve energy and spectral efficiencies compared to the related work by more than 75%, in addi-
tion to the dynamism of the introduced mechanism. This system reduces the transceivers’ hardware
and computational complexity while improving reliability and transmission rates, without the need
for complex technologies, e.g., multi-input multi-output or reflecting services.
Keywords: 6G wireless communications; cooperative networking; energy/spectral efficiencies;
energy harvesting; H-NOMA; outage probability; SWIPT-pairing; THz
1. Introduction
Current wireless communication systems lack to meet the new requirements of the
ever-updating next generations. This requires compulsory integration of the leading edge
of promising technologies and intelligent applications to comply with distance-depend-
ent terahertz (THz) constraints. It is essential to develop a suitable capable communication
system to satisfy the expected features and demands, i.e., ubiquitous connectivity, su-
preme SE, minimal latency, huge data rate, system robustness, user fairness, supporting
emergent applications, energy efficiency (EE), spectral efficiency (SE), and cost-effective-
ness. Revolutionary research across the world has identified THz frequencies as the future
of wireless communications [1–3]. EE and SE are pivotal factors to assess and enhance
communication systems to satisfy the emergent essential 6G applications [4–7]. EE is an
essential criterion in the next era of wireless communications and its overwhelmed infra-
structure due to the rising power consumption of the required elements to connect a huge
number of devices supporting the principle of the internet-of-everything (IoE) [8–13].
Hence, EE in 6G communications is mandatory to save energy and meet the practicality
of 6G communication networking [14]. As a critical topic, terahertz communications (0.1–
10 THz) has attracted great attention from the research community, playing a very im-
portant role in 6G and generations beyond. SE depends on the availability of bandwidth
Citation: Oleiwi, H. W.;
Al-Raweshidy, H. SWIPT-Pairing
Mechanism for Channel-Aware
Cooperative H-NOMA in 6G
Terahertz Communications.
Sensors 2022, 22, 6200.
https://doi.org/10.3390/s22166200
Academic Editors: Sotirios K.
Goudos, Dimitris E. Anagnostou,
Panagiotis Sarigiannidis,
Konstantinos E. Psannis, Shaohua
Wan and Stavros Koulouridis
Received: 21 July 2022
Accepted: 16 August 2022
Published: 18 August 2022
Publisher’s Note: MDPI stays neu-
tral with regard to jurisdictional
claims in published maps and institu-
tional affiliations.
Copyright: © 2022 by the authors. Li-
censee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and con-
ditions of the Creative Commons At-
tribution (CC BY) license (https://cre-
ativecommons.org/licenses/by/4.0/).
Sensors 2022, 22, 6200 2 of 19
(BW) and working frequency. It is the backbone of the next wireless communications era
given its valuable features as well as the various services that THz provides [15]. THz
communication complements mmWave and optical bands as an alternative to fiber optics
links of certain use cases, i.e., backhaul to backhaul/fronthaul, kiosk-users, data-centers
internal links, internal device links, and THz-to-fiber links [16]. However, absorption and
path losses effects of THz frequencies divide the spectra into spectral bands that are being
explored to comply with 6G communication services [17]. The new generation's ubiqui-
tous coverage necessitates a revolutionary upgrade to the existing systems toward estab-
lishing robust and reliable wireless systems with extraordinary capabilities.
To this end, this paper is motivated by the capability of integrating the evolutionary
technologies and developing a channel-aware path selection mechanism, targeting the es-
tablishment of a reliable and scalable simplified system by the enhancement of band-
width-competitive 6G THz communications, and overcoming the constraints of the cur-
rent resource-scarce systems. Moreover, this work optimized the existing communication
systems by adopting hybrid-NOMA, THz with cooperative SWIPT technologies to com-
ply with the intended goals, highlighting the attained gains. The paper’s contributions to
knowledge are:
(1) We designed a modified integrated (energy and spectral efficient) wireless communi-
cation system with powerful capabilities for the green communications era. It applies
6G candidate technologies to take full advantage of their characteristics for sufficient
performance.
(2) We utilized the practical application of hybrid-NOMA to the proposal for the utmost
benefit of this scheme over single-carrier NOMA shortages.
(3) We evaluated the best pairing strategy in H-NOMA to attain the best possible system
performance.
(4) We proposed a cost-effective simplified system, provided with a single input–single
output high-directional antenna instead of other complexed schemes, to reduce com-
putation and signal detection complexities in the receiver, maintaining sufficient SE,
reducing power consumption, and increasing EE.
(5) We investigated all the possible SWIPT pairs with the available (LOS) users to specify
the best pair that provides the best performance.
(6) We developed a dynamic mechanism to select the best SWIPT-pairing user out of all
available users to guarantee fast and accurate dynamism.
(7) We modified a scalable and upgradeable system while setting adjustable factors, i.e.,
coverage area, transmit power, carrier-frequency, bandwidth, and the simplest mod-
ulation.
The rest of the paper is structured as follows: Section 2 presents a brief background
of the introduced system technologies. Section 3 compares a number of interesting previ-
ous works, explaining the intended objectives, followed by the paper's contributions. Sec-
tion 4 describes the proposal and addresses mathematical derivatives. It argues the idea
behind proposing this system and the beneficial points. In Sections 5 and 6, mathemati-
cal/simulation results are conducted and discussed, showing the outperformance of the
proposed system over the state-of-the-art systems. In the end, we conclude this paper in
Section 7.
2. Background
To meet the potential technical specifications, non-orthogonal multiple access
(NOMA) is a strong candidate to be integrated with the 6G paradigm [18]. It enables the
evolution of SE, outperforming the earlier strategies of orthogonal multiple access (OMA)
in terms of SE, channel capacity, resource management, user-fairness, massive connectiv-
ity, and lower latency. The main procedure of NOMA is to carry out superposition coding
combining users' signals at the transmission end (Tx), where it must be realized and
treated using successive interference cancellation (SIC) as a multi-user detection at the
Sensors 2022, 22, 6200 3 of 19
receiving end (Rx) to discard any interference. It enlarges the channel capacity, which re-
lies on the channel bandwidth. This paper concentrates specifically on hybrid-NOMA (H-
NOMA). Based on NOMA fundamentals, various power coefficients are allocated to the
users based on their channel state information (CSI) and multiplex them in the power
domain. To improve SE and eliminate complexity, user-clustering is important in THz
NOMA communications based on users’ locations or other metrics. However, to reduce
the complexity of clusters in some cases, only one main user’s CSI might be set as a refer-
ence for the remaining number of users within the NOMA cluster [18]. In the SISO-NOMA
scheme, both BS and users are equipped with a single antenna that relies on CSI for users'
sorting, preparing them to implement better SIC at the receiving end. The larger the chan-
nel condition differences among users, the better NOMA performance we obtain [19]. H-
NOMA is an integration of NOMA/OMA techniques. It is proposed to overcome the chal-
lenges or limitations that undermine the performance of those systems, e.g., the complex-
ity and possibly of interference due to the huge number of users. The strategy of CSI ac-
quisition is very important to determine the procedure and sequence of SIC; however, SIC
is not CSI-based only, as there are QoS-based, hybrid-based, or other procedural SICs
based on other strategies [20]. Due to the lack of transmission distance and the losses in
THz communications, it is recommended to adapt NOMA-assisted cooperative network-
ing to tackle those problems. Cooperative network relaying offers more reliability and
capacity, enhancing the overall performance, especially when integrated with other mod-
ern technologies such as NOMA. NOMA’s SE can be improved using cooperative net-
working for better support to the blocked users or users with a weak signal-to-noise ratio
(SNR) with THz communication, especially with the merging energy harvesting (EH)
technique with cooperative NOMA [21], which the paper studies with THz frequencies.
Reasonably, using cooperative networks will cause battery drainage of relaying of the
user’s device. In addition, the terahertz-NOMA system experiences the burden of high
computations of SIC at Rx; therefore, to comply with that problem, it is logically recom-
mended to apply the EH technique [22]. Applying EH will exploit the radio frequency
(RF) signals’ energy that surrounds most of the devices, e.g., energy belonging to other
destinations. Using EH enables the relaying user to harvest that energy to use it again to
retransmit the targeted user’s signal. In power splitting-based EH, the relaying user splits
the received signal’s power into an EH partition (ψ) and an information-decoding parti-
tion (1-ψ) to carry out EH and information-decoding at the exact time, i.e., simultaneous
wireless information and power transfer (SWIPT) [23], as demonstrated in Figure 1.
SWIPT enhances system capacity, outage probability (OP), and accordingly EE. It repre-
sents one of the potential technologies for physical layer optimization [24].
Figure 1. SWIPT with DF-relayed NOMA.
3. Related Works
Sensors 2022, 22, 6200 4 of 19
In recent years, cooperative networking has been studied in several cases and scenar-
ios, and its fruitful use has already been demonstrated. There are some disadvantages of
using cooperative networks stated with wireless communications. Integrating the NOMA
scheme and THz communications to attain a positive impact on wireless communications
was explored thoroughly, showing the impairments, weaknesses, limitations, and the
shortage of performance in academic and industrial environments. THz communications
of [25], despite using intelligent reflecting surfaces (IRS) to improve the transmission be-
tween Tx and Rx, had to outperform the cooperative networks by all the means, simplic-
ity, EE, and cost, not only optimizing reflectors but also to consider all other criteria, e.g.,
to minimize power consumption and to maximize EE. In [23], the authors presented im-
portant points, considering disadvantages of IRS design and deployment as a new tech-
nique to support 6G infrastructure, i.e., controlling instantaneous beam steering, interfer-
ence, and EE. It also addressed the challenges of IRS deployment, i.e., (1) design and con-
trol joint communications components, required procedures and analyses, hardware im-
pacts, on performance, total cost, required space for deployment, and the continuous
maintenance; (2) potential failure influences because of environment or accidents; (3) IRS
interactivity with the transmission instantaneous changes; and (4) IRS complexity as an
additional computational burden. The authors in [26] explored grouping and pre-coding
with energy optimization. They suggested a different way of user-clustering of THz mul-
tiple-input multiple-output (MIMO)-NOMA design by building an algorithm of artificial
intelligence. In [27], the author proposed MIMO-based spatially multiplexed work by
adopting a new index-modulation scale. He studied the MIMO technique to build ultra-
throughput/SE systems. In [28], the energy allocation problem was studied with coopera-
tive half duplex/full duplex MIMO-NOMA with THz for maximizing the data rates of
users.
In the author's recent work [1,2], similar integrated systems were proposed for SISO-
NOMA and MIMO-NOMA, respectively. However, those papers did not consider chan-
nel awareness to propose a dynamic channel selection mechanism for a SWIPT-pairing
near user, whereas the work in [3] studied SISO-H-NOMA from a clustering point of view
without presenting a suitable mechanism to fulfill the gap.
Moreover, in a recent paper [29], the author investigated the role of multihoming and
other essential enabling techniques in improving the performance of communication sys-
tems, whereas in a previous article [30], we looked into the influence of the multihoming
concept on system reliability, efficiency, and performance, focusing on the importance of
the multihoming strategy in maintaining communication of the multihomed users.
Based on the authors' knowledge, the THz-based modified adaptable system has not
been proposed yet concerning the cost/complex-to-performance trade-off. There have not
yet been similar simplified and feasible mechanisms presented for optimum performance.
4. Methodology
This section is divided into two sub-sections; the first section studies hybrid-NOMA-
pairing possibilities and optimizes the optimal pair to the associated users within the cell,
whereas the second section studies the best SWIPT-pairing for the farthest blocked user
(or distant cell-edge users). The main system model is shown in Figure 2; hence, some of
the mathematical derivations were developed from our previous analysis in [1–3]. Table
1 describes the symbols of all the mathematical equations.
Sensors 2022, 22, 6200 5 of 19
Figure 2. Main system model.
Table 1. Mathematical equation symbols.
Symbols Description
AWGN Additive white Gaussian noise
AWGN variance
PDF Probability density function
P Transmit power
αn Power coefficient of the near user
αf Power coefficient of the far user
NU Near user
FU Far user
Signal of the near user
Signal of the far user
R Relaying user
H A vector of Rayleigh channels for k-number of users
K Constant
N–N Near–near
F–F Far–far
h2, h3, and h4 Rayleigh fading channels of user2, user3, and user4
A Number of antennas
G Antenna-gain
η THz source-to-destination losses
f
Frequency
d
Source-to-destination distance
a(f)
Absorption coefficient
c
Speed of light
hsn
BS-to-NU Rayleigh channel (mean = 0, variance = dsn-η )
dsn
BS-to-NU transmission distance
wn
AWGN
weh
Thermal noise (zero mean, variance = )
ζ
Electronic circuits' EH efficiency
hnf
NU–FU Rayleigh fading channel
δ
A very small value of 10
ψ
The energy harvesting power fraction
Sensors 2022, 22, 6200 6 of 19
The transmission is considered over Rayleigh channel (mean = 0, variance =
Transmission Distance-THz losses ) with additive white Gaussian noise (AWGN) (mean = 0,
variance = . The probability density function (PDF) of a certain point is given by:
(;)=1
√2−
2
(1)
4.1. The Best Hybrid-NOMA Strategy
In this sub-section, we studied the impact of the user-pairing scheme in NOMA–
OMA multiple access (Figure 3) to be adopted for the next SWIPT-pairing sub-section.
Figure 3. Hybrid-NOMA pairing strategy.
4.1.1. Near–Far pairing (N–F)
With the N–F strategy, the nearest user to the BS (User4) pairs with the farthest user
(User1). BS’s nearer user (User3) pairs with the second farther user (User2). Thus, in this
strategy, User4 and User1 are paired in the first block, whereas User3 and User2 are paired
in the second block.
Within the first pair, User4 represents the near user (NU), while User1 is the far user
(FU); however, power coefficients are required to be allocated by setting α4 < α1. Thus,
User4 requires SIC implementation before detecting its intended signal, while User1 de-
codes its intended signal directly without SIC. Within the second pair, User3 represents
NU, whereas User2 represents the FU; however, power coefficients must be allocated by
setting α3 < α2. Thus, User3 implements SIC, whereas User2 detects its intended signal
directly.
In pair 1, the rates of the users are given by:
4, = 1
21+
Pα
4|ℎ4|
(2
)
1, = 1
21+
Pα
1|ℎ1|
Pα
4|ℎ1|+
(3)
Similarly, for the second pair:
3, = 1
21+
Pα
3|ℎ3|
(4)
Hence, P denotes transmit power, αn and αf are power coefficients of the near user
and far user, respectively, and and denote the signals of the near user and far user,
respectively.
Sensors 2022, 22, 6200 7 of 19
The far user is not able to detect its signal because of the blockage; however, the signal
of the near user is:
2, = 1
21+
Pα
2|ℎ2|
Pα
3|ℎ2|+
(5)
NU’s rate is given by:
Rnf = R1,nf + R2,nf + R3,nf + R4,nf (6)
4.1.2. Near–Near, Far–Far Pairing (N–N, F–F)
The N–N, F–F strategy addresses that User4 pairs to User3, whereas User2 pairs to
User1. This strategy pairs User4 to User3 and User2 to User1 for the two blocks.
In this strategy, U4 is NOMA NU as compared to U3. Therefore, we must allocate α4
< α3. User4 requires SIC implementation before detecting its intended signal, while User3
decodes its intended signal directly without SIC. In the other block, U2 is NOMA NU as
compared to U1. Accordingly, we must allocate α2 < α1. Thus, User2 performs SIC and
User1 decodes directly.
The rates in the first block are given by:
4, = 1
21+
Pα
4|ℎ4|
(7)
3, = 1
21+
Pα
3|ℎ3|
Pα
4|ℎ3|+
(8)
Similarly, for the second pair:
2, = 1
21+
Pα
2|ℎ2|
(9)
1, = 1
21+ Pα1|ℎ1|
Pα
2|ℎ1|+
(10)
The NU rate is given by:
Rnn = R1,nn + R2,nn + R3,nn + R4,nn (11)
4.2. The Best SWIPT-Pairing Mechanism
In this sub-section, we study SWIPT-pairing with three scenarios of pairing using one of
the three available LOS near users (U4, U3, or U2) to be the DF relay pairing user with the
targeted far user (U1), and then we develop a suitable mechanism to select the best SWIPT-
pairing user using the minimum (min) function to find the lowest (nearest) channel fading of
the available LOS users to be paired with the blocked farthest user to achieve the highest chan-
nel gain difference for the optimal NOMA pair. Otherwise, the mechanism selects the second-
lowest fading (second-near) user, and so on.
Based on the Rayleigh fading equation, we propose a mechanism of selecting the best
pairing user to act as a relay to user1, and we set the minimal Rayleigh fading channel
R = min{
}
(12)
where R is the selected relaying user, and H is a vector of Rayleigh channels for k-number of
users; however, we propose k = 4.
Based on NOMA principles, the selected user is the NU (DF relay user), whereas the
blocked user is the FU.
In the proposed system model, as we have 3 LOS available users with FU, the NU selec-
tion mechanism is expressed as
Sensors 2022, 22, 6200 8 of 19
NU = min{h2,h3,h4} (13)
where h2, h3, and h4 denote the Rayleigh fading channels of user2, user3, and user4, respec-
tively, (each with its distance with the BS).
The proposed mechanism (shown in Figure 4) works in spacious open areas such as rural
territories or the countryside (i.e., it is not possible to deploy other network equipment to aid
THz communications). The system considers a downlink THz NOMA-based single-cell serv-
ing 4 users, where all the parties are provided with single highly directed antennas. The trans-
mitter party (BS) combines users' signals to broadcast them to the receivers (i.e., various chan-
nel-conditioned users) including the paired user (NU and FU), where we assume there is an
existing obstacle blocking the BS-U1 link. Accordingly, U1 cannot receive the signal efficiently.
The potential NU (U4, U3, or U2) has a sufficient channel gain. Based on NOMA, the signal of
the FU is decoded and canceled by the NU implementing SIC before decoding the NU infor-
mation signal. It is worth noticing that NU receives and decodes FU’s signal. Therefore, NU
could aid FU’s connection as a DF-relay. To this end, the NU's device power does not suffice
to retransmit FU’s signal. Thus, we suggest that NU performs SWIPT to harvest energy from
radio-frequency energy surrounding it. The communication process is carried out in two
phases; the sender's combined signal is received by NU in the initial phase. By adopting the
power splitting technique, a portion of the received power will be captured, and the remaining
power will be used for information decoding. The captured power is then used by NU to re-
transmit the signal to the FU.
Figure 4. Cooperative SWIPT hybrid THz NOMA model.
The proposed system takes into consideration THz frequency characteristics and
losses. Transmission link loss in the non-line-of-site path (NLoS) is much more than link
loss in line-of-site (LOS); thus, the NLoS impact could be neglected when LOS governs
[1]. In this paper, THz losses (η) are presumed to be very high. The channel gain can be
calculated as:
ℎ=√
(14)
Hence, A denotes antenna number, G refers to antenna gain, and η denotes
THz source-to-destination losses, given by:
=(4
)()
(15)
Hence, f denotes frequency, d denotes source-to-destination distance, a(f) denotes ab-
sorption coefficient, and c denotes light speed.
The derived closed-form according to the proposed scenario is:
Stage 1: The transmission of the superimposed signal in the first stage is shown as
= √
P
(√
+
(16)
Sensors 2022, 22, 6200 9 of 19
where P denotes transmit power, αn and αf are the power coefficient of NU and FU, re-
spectively, and xn and xf are the power signal of NU and FU, respectively. Due to the
blockage, FU is not able to receive its signal, whereas the received signal at the NU is given
by
= √
P
(√
+
)ℎ +
(17)
Hence, hsn represents the BS-to-NU Rayleigh channel (mean = 0, variance =
dsn-η ), dsn denotes the BS-to-NU transmission distance, and wn refers to AWGN (mean
= 0, variance = ). Out of yn, NU extracts a portion of power as the EH coefficient (ψ).
The rest of the energy (1 − ψ) is allocated to decode its data, which is represented by:
D=(
(1-ψ)
) + ℎ
=(
(1-ψ
) √P (√ + ) + ((
1-ψ
) ) + ℎ
(18)
Hence, weh refers to thermal noise (zero mean, variance = ). The tiny EH value of
wn can be neglected; thereby yD will be:
D=(
(1-ψ)
)√P (√ + ) + ℎ
(19)
From (17), NU decodes xf directly first. The achievable rate of the decoded FU’s data
by the NU is
= 1
21+
(1-ψ)P αf
|ℎ|
(1-ψ)P α
|ℎ|+
(20)
By implementing SIC, NU’s rate is given by:
= 1
21+
(1-ψ)P αn
|ℎ|
(21)
The harvested energy during phase 1 is represented by:
= |ℎ| ζ
ψ (22)
Hence, ζ denotes the electronic circuits’ EH efficiency.
Phase 2: In the next phase, by allocating the harvested energy (PH), NU retransmits
the data meant for FU. Consequently, NU's sent signal is:
√
PH
(23)
Accordingly, the signal at FU is given by:
√
PH
ℎ +
(24)
where hnf denotes the NU–FU Rayleigh fading channel. The achievable rate at the FU is
= 1
21+|ℎ|
(25)
In order to evaluate the ideal value of the EH-coefficient, NU requires FU information
decoding. Next, it can effectively convey the FU signal. Thus, the constraint Rnf > Rf∗ is
set.
Hence, Rf∗ represents the targeted rate of FU. Addressing that the NU rate to decode
the FU signal must be greater than that of F. in (21) with the set condition is swapped
to produce ψ
1+
(1-ψ)P αf
||
(1-ψ)P α
||
> Rf ∗
(26
)
1+ (1-ψ)P αf |ℎ|
(1-ψ)P α
|ℎ|+
> 2Rf ∗
(27
)
Sensors 2022, 22, 6200 10 of 19
(1-ψ)P αf |ℎ|
(1-ψ)P α
|ℎ|+ >2∗ −1
(28
)
We denote 22Rf* − 1 to be τf, representing the targeted value of FU’s signal to inter-
ference plus the noise ratio.
(1-ψ)P αf
|ℎ|
(1-ψ)P α
|ℎ|+ >
(29
)
(1-ψ)
|ℎ|>
(1-ψ)P α
|ℎ|+
τf
(30
)
(1-ψ)
|ℎ|−
(1-ψ)P α
|ℎ|>
τf
(31)
(1-ψ)
|ℎ|
(αf-τfα
)
>
τf
(32)
ψ
<
1 − τf
P
|ℎ|
(αf-τfα
) (33
)
Verifying the constraint of ψ in (33), the equation is reformed as:
ψ
= 1 −
τf
P
|ℎ|
(αf-τfα
)
−
(34)
Hence, δ refers to a very small value of 10; however, ψ represents the energy needed
to decode information to attain the intended rate of FU.
The outage probability (OP) is the possibility of the data rate of the user falling below the
targeted value. We assume Rn∗/Rf∗ as the target rates of NU/FU, respectively.
FU is in OP when the Rf rate of (25) falls underneath the targeted value, given by:
PFU = Pr(Rf < Rf∗) (35)
NU decodes both signals accurately. Hence, both targeted levels must be equal to or
greater than that of NU. By performing SIC, NU faces OP when both values in (21) and (25)
do not meet that value of NU, mathematically given by:
PNU = Pr(RNF < Rf∗)
+
Pr(RNF > Rf∗, Rn < Rn∗) (36)
Based on the IEEE standard in [31], and according to the available terahertz spectral
bands, ref. [32] divided the gap into certain channels and bandwidths (approved globally), allo-
cated BW depending on the system compatibility, application requirements, hardware limita-
tion, and transmission conditions.
In THz-SC PHY, BPSK and QPSK modulation schemes are mandatory; thus, we adopt
the simplest scheme (BPSK) to improve system performance and mitigate the complexity, as
increasing the modulation index, i.e., signal levels, leads to a greater bit error rate (BER) in
addition to increasing the processing time and latency (this work achieves higher SE depend-
ing on the integrated technologies' capabilities without the need for high-order modulation
schemes). Moreover, the planner must utilize coverage distance with system performance to
gain the trade-off between range and rate [31].
4.3. Optimal SWIPT-Pairing
The mechanism of the best SWIPT-pairing adopts the principle of the best channel-con-
ditions difference between the targeted blocked user and the paired user. A higher distance
between them causes a higher channel condition difference, which means better NOMA per-
formance, especially when the available relaying NU locates at the closest point with regards
to Tx. To gain an ideal channel difference, the farthest targeted user requires pairing with the
nearest user to the BS, which is preferred to SWIPT; if that is not achievable, then the second
nearest user to the BS must be tried, and so on. Then for the next pairing, the targeted user
does the same procedure to find its pair starting from the nearest possible user to BS and far-
thest from itself. The blocked user will find the best available user for the optimal cooperative
SWIPT scenario.
Sensors 2022, 22, 6200 11 of 19
5. Implementation Environment
This work was simulated as the following (parameters of [30]): Firstly, we simulated
and compared the performance with mathematical analysis to demonstrate the viability
of employing H-NOMA to replace NOMA to achieve the intended objectives in order to
gain the most advantages in comparison with NOMA and OMA. After that, we evaluated
the paper's core case to examine the three potential SWIPT pairs to the obstructed user
(User1) and analyze each pair's performance using parameter settings for frequency,
bandwidth, transmit power, and transmission distance. Then we developed a suitable
mechanism to select the optimal DF relaying user (NU) to the intended U1’s pairing. The
system was simulated using MATLAB. Table 2 shows the simulation parameters.
Table 2. Simulation parameters.
Symbol Parameter V.A V.B
f Frequency 311.04 GHz 311.04 GHz
BW Bandwidth 12.96 GHz 12.96 GHz
P Transmission power 20-40 dBm 30 dBm
d Transmission distance U1, U2, U3, U4 = (10, 9, 4, 3) m
αn NU power coefficient 0.2 of total power
αf FU power coefficient 0.8 of total power
G Antenna gain 25 dB
eta Path loss exponent 4
Targeted data rate 1 Gbps
EH conversion efficiency 0.7
We investigated system performance based on the influential THz factors. The sug-
gested technique should make it possible for the obstructed user to continue communi-
cating while being shadowed, failing to connect to BS. The ability to regulate THz short-
falls was then explored, demonstrating how this could enhance SE, EE, stability, and the
entire efficiency. The modeling findings supported the optimized system's obtained
closed form and was compared to that of previous work. Table 3 describes hybrid-NOMA
strategies.
Table 3. Hybrid-NOMA strategies.
Users/Time Multiple Access
Technique Strategy Time Slots
U1, U2, U3, and U4
TDMA U1 U2 U3 U4 4
NOMA U1, U2, U3, and U4 1
NOMA\TDMA First Pair Second Pair 2
Time 4 ms.
6. Results and Discussion
The system simulation and analysis were carried out to prove the validity of the en-
hanced achievable rates and outage probability. All possible SWIPT pairs were studied.
6.1. H-NOMA, NOMA, and OMA Performance Comparison
The simulation of H-NOMA strategies was carried out in comparison to traditional
single-carrier NOMA (SC-NOMA) and TDMA (Figure 5) in order to verify the rationale
for selecting the optimal scheme among the MA techniques according to Figure 3 and
Table 2.
Sensors 2022, 22, 6200 12 of 19
Figure 5. H-NOMA techniques vs. NOMA/OMA.
Based on Figure 5, whenever the channel-condition divergence of NOMA users is
distinctive, we can observe that the (N–F) approach works better than other methods in
some circumstances, significantly with THz, confirming that we can fully utilize NOMA
in those situations. NOMA still outperforms TDMA with the (N–N, F–F) method, alt-
hough not significantly better. Due to interference brought on by too many users using
the same carrier, SC-NOMA's performance is still insufficient. This leads to problems with
complexity and interference. Consequently, employing a single carrier while increasing
the number of people served is not recommended.
6.2. Proposal Simulation
To analyze system performance and compare it to the related work, and to show how
this proposal presents an important improvement to wireless communications by utiliz-
ing the key-enabling techniques, we simulated the proposal for each potential relaying-
user through 3 sections.
Figure 6 shows the average achievable rate of near and far users for the three possible
SWIPT pairs, namely, U2–U1 (a), U3–U1 (b), and U4–U1 (c). We noticed that as a result of
the EH mechanism, which utilized only the necessary power to achieve the required rate,
capturing all the remaining power, NU peaked at 1 Gpbs/Hz. Increasingly, in (a), (b), and
more in (c), NU achieved a better data rate, exceeding the target for the same power split-
ting ratio we used because of the lower distance (better SINR) from the BS, achieving bet-
ter sum-throughput and SE accordingly. The FU rate increased without affecting NU sta-
bility by using the available harvested power in all cases; however, we could make use of
the overused FU available energy for more EH operations. The best overall performance
resulted in the U4–U1 SWIPT pair (c).
Sensors 2022, 22, 6200 13 of 19
(a) (b)
(c)
Figure 6. Average rate versus transmission power.
6.2.1. OP versus Transmission Power
We notice from Figure 7 that FU showed higher OP than that of NU in all cases, alt-
hough having higher rates of FUs as compared with NU. The best overall performance
resulted in the U4–U1 SWIPT pair (c) as compared to those of (a) and (b) due to the greater
channel difference between the NOMA near and far users (preferable). This supports the
idea behind this work to assist the distant, the weak-conditioned, and the path-blocked
users.
(a) (b)
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(c)
Figure 7. OP versus transmission power.
6.2.2. Instantaneous-Rate versus Channel-Realization.
To study the performance of the SWIPT pairs accurately, we examined the instanta-
neous rates under channel realization.
In Figure 8, we still observe that FU did not show better stability compared to NU in
all the cases despite the larger power and data rate; FU’s instantaneous rate was gaining
the same level as that in Figure 6 and some variations below the targeted level, which
explains the variety of users' performance. The best overall performance resulted in the
U4–U1 SWIPT pair (c).
(a) (b)
(c)
Figure 8. Instantaneous-rate versus channel-realization.
Sensors 2022, 22, 6200 15 of 19
It is worth noting that the proposed system delivered a remarkable enhancement
over that of [21] using simpler requirements and lower power/cost, and it gained higher
SE and EE. It achieved better performance, showing the importance of EH and the
emerged techniques.
6.3. Optimal SWIPT-Pairing Mechanism
In this section, we simulated the system model using the mechanism in (12) to select
the best SWIPT partner to act as a DF relay to U1 out of the available LOS users, using the
same parameters as in Sections 4 and 5.
6.3.1. Average Rate versus Transmission Power
Figure 9 illustrates how the aforementioned mechanism ran the best SWIPT-pair with
the best performance, resulting in U4–U1 pair selection. This describes the importance of
the channel condition difference between the paired NOMA users (NU and FU); the
greater the channel difference, the better the NOMA performance. The privilege of selec-
tion dynamism was obtained by the proposed mechanism.
Figure 9. Average rate versus transmission power.
6.3.2. OP versus Transmission Power
Similarly, Figure 10 shows how the same mechanism managed to select the best
SWIPT pair with the best outage probability, resulting in the selection of the U4–U1 pair.
It improved overall system reliability and OP by aiding the targeted user to opt for the
best NU to pair with in terms of NU location and, accordingly, channel condition differ-
ence.
Figure 10. OP versus transmission power.
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6.3.3. Instantaneous Achievable Rate versus Channel Realization
To make sure that the proposed mechanism achieves accurately the best performance
for users, Figure 11 above illustrates the simulation of the instantaneous achievable rates
under channel realization. Once again, it is clearly shown that the proposed mechanism
leads to the best user and overall performance accordingly by selecting the best pair to
achieve the intended goal.
Figure 11. Instantaneous-rate versus channel realization.
6.4. System Numerical analysis and Simulation
We compared the proposal's sum throughput and OP using simulations and analysis
to prove the validity of the closed-form of the system model, leading to the preplanned
objectives, utilizing similar input parameters, and setting a transmission power of 20 dBm.
6.4.1. Sum Throughput versus Transmission Power
Based on the same parameters used to examine the validity of mathematical deriva-
tions, Figure 12 shows considerable matching with the system simulation.
Figure 12. Sum throughput versus transmission power.
6.4.2. User OP versus Transmission Power
Similarly, Figure 13 verifies the feasibility of mathematical analysis by conducting a
point-to-point comparison and setting the exact parameters. It shows noticeable matching.
Sensors 2022, 22, 6200 17 of 19
Figure 13. User OP versus transmission power.
Remarkably, Figures 12 and 13 depict clear consistency of both results, which confirm
the accuracy of the analyses and system model validity of achieving the objectivity and
novelty of the proven added values.
7. Conclusions
To meet the 6G stringent specifications, this work was carried out to fulfill the miss-
ing gap of 5G research and standardization, emphasizing the THz communication chal-
lenges. The optimal THz H-NOMA pairing approach for each user serviced was first ex-
amined in this paper. The outcomes demonstrated a substantial approach to overcoming
SC-NOMA and THz limitations in order to accomplish the planned goals and adapt to the
prospective wireless systems of the following generations. Then, a thorough analysis of
all potential SWIPT-pairing prospective users of the cooperative THz H-NOMA was con-
ducted. The closest user to the BS that offered the best system performance among all the
available users was practically demonstrated to be an efficient SWIPT DF-relaying user.
Moreover, the paper stated the significance of proposing such a mechanism, examining
the feasibility of its management to opt for the optimal pair depending on users’ locations
and SINR to develop an efficient system, achieving the best overall performance, e.g.,
maximum achievable EE/SE, using the merged technologies. It showed an improvement
in overall performance when compared to the systems in use today (EE/SE are improved
by 75 percent) in addition to the dynamism of the introduced mechanism, incorporating
all the comparison criteria. The overall results proved the validity of the proposed tech-
niques to maintain the reliability of ongoing THz communications, and the leverage of the
developed mechanism to improve the system performance and precision almost perfectly.
Finally, we examined the accuracy of numerical and simulation results that showed per-
fect matching. Further work must be done to automate the computational and procedural
operations using artificial intelligence algorithms.
Author Contributions: Conceptualization, H.W.O.; Supervision, H.A.-R. All authors have read and
agreed to the published version of the manuscript.
Funding: This research received no external funding.
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Data Availability Statement: Not applicable.
Conflicts of Interest: The authors declare no conflict of interest.
Sensors 2022, 22, 6200 18 of 19
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