Non-orthogonal Multiple Access Networks Research Articles

Improving the security of NOMA cognitive networks

Aiming at the scenario where the eavesdropper try to eavesdrop on the confidential messages of secondary trusted users, two physical-layer network coding (PNC) strategies, namely dual power superposition (PS-PS) encoding strategy and bit-level exclusive-or power superposition (XOR-PS) encoding strategy, are proposed to improve the security performance of cognitive non-orthogonal multiple access (NOMA) networks with the help of the data transmitted by the primary user. Considering the overlay spectrum sharing mechanism and the imperfect successive interference cancellation (SIC) technology, we first derive the closed-form accurate expressions of the outage probability and intercept probability of the secondary network with these two schemes over Rayleigh fading, and also give the asymptotic outage probability in the high signal-to-noise ratio (SNR) regime. Then, the correctness of the theoretical results is verified by simulation. For comparison, we also use the scheme without the assistance of the primary user as the benchmark scheme, which is represented by NPS. Finally, the simulation results show that the security of the proposed PS-PS and XOR-PS schemes is much better than that of the NPS scheme in the case of without reducing the outage performance.

Physical layer security for confidential transmissions in frequency hopping-based downlink NOMA networks

Facing the exponential number of Internet of Things (IoT) devices and the scarcity of available resources, next-generation wireless networks have to meet very challenging performance targets in terms of providing massive access and ensuring higher spectral efficiency. In this vein, Non-Orthogonal Multiple Access (NOMA) has been widely recognized as one of the advantageous techniques to handle the proliferation of the IoT. Nevertheless, from a security standpoint, enabling a user to decode the signals of the other users, while using Successive Interference Cancellation (SIC), raises serious concerns regarding confidentiality and vulnerability to malicious attacks. Meanwhile, conventional security paradigms, such as upper-layer encryption and sophisticated authentication mechanisms, require high computational complexity and additional processing, which impose an overwhelming burden on energy-efficient IoT devices. Alternatively, Physical layer Security (PLS) has sparked a significant interest as a promising complement to cryptographic techniques. The key idea of PLS is to avail wireless communication properties to secure communications without adding complex encryption mechanisms at higher layers. In this paper, we propose a PLS approach based on a network coding technique to prevent eavesdroppers from decoding users’ information transmitted through a downlink-based NOMA system. This results in correlating the packets to be transmitted with each other, making the interception of a single packet useless. We demonstrate that the eavesdropper’s decoding complexity increases exponentially with the sequence length, making the task intractable for relatively long ones.

Performance analysis of shared relay CR-NOMA network based on SWIPT

With the development of wireless communication technology, the number of devices accessing the communication network is increasing. This paper addresses critical issues such as low spectrum resource utilization and the energy constraints of devices. The investigation focuses on the system performance of the shared relay Cognitive Radio Non-Orthogonal Multiple Access (CR-NOMA) network based on Simultaneous Wireless Information and Power Transfer (SWIPT) network model. Unlike the existing CR-NOMA model in which the secondary network user do not participate in the transmission of information from the primary network, we consider the secondary network near user as shared relay. The shared relay utilizes SWIPT technology to harvest energy using a nonlinear energy harvesting model. Additionally, the shared relay assists in transmitting information from the primary network base station to primary user, as well as from the secondary network base station to far user of the secondary network. Subsequently, we conduct a series of simulations to analyze the effects of Signal-to-Noise Ratio (SNR), power distribution factor, interference threshold, and time-switching (TS) factor on system performance. Furthermore, we compare and analyze the performance of our proposed network model against CR-NOMA network across three dimensions: outage probability, throughput, and energy efficiency. Our results demonstrate that the proposed network model exhibits superior outage performance and enhances user throughput compared to the CR-NOMA network. Additionally, it demonstrates improved energy efficiency compared to the shared relay CR-NOMA network, leading to an overall improvement in network performance.

Enhancing vehicular NOMA communication security through reconfigurable intelligent surfaces

Physical layer security (PLS) aims to ensure the confidentiality and authenticity of transmitted data by capitalizing on the inherent randomness of wireless channels. Owing to the popularity of intelligent transportation systems (ITSs), PLS research has sparked renewed interest in the wireless research community. This paper investigates the performance of secure communication in the context of a vehicle-to-vehicle (V2V) communication scenario by employing a reconfigurable intelligent surface (RIS). Further, we introduce the concept of non-orthogonal multiple access (NOMA) to reduce latency and improve communication efficiency in V2V networks. This study aims to comprehensively analyze secrecy performance, encompassing parameters like average secrecy capacity (ASC), secrecy outage probability (SOP) and probability of non-zero secrecy capacity (PNZSC). Our research aims to highlight the efficacy of RIS in providing secure and reliable communication within V2V NOMA networks. Ultimately, our study contributes to advancing secure communication protocols in intelligent transportation systems.

Adaptive-Duplex Relay Selection for Cooperative Non-Orthogonal Multiple Access Networks

To further improve the spectral efficiency of the cooperative non-orthogonal multiple access (NOMA) network with half-duplex (HD) relaying and avoid the zero diversity gain due to the imperfect self interference estimation at high signa-to-noise ratio (SNR) value with full-duplex (FD) relaying, this paper developed a novel two-stage relay selection for a two-user multi-relay cooperative NOMA systems with adaptive-duplex (AD) relaying which can switch opportunistically between HD and FD relaying modes. An adaptive duplex based on fixed power allocation factor relay selection (AD-FPA-RS) scheme for cooperative NOMA networks is proposed in this paper, the relay can switch the work mode to the FD or HD state adaptively according to the current channel state information and the result of decode at the relay. Futhermore, the exact outage probability for the proposed AD-FPA-RS scheme is obtained in closed-form expression. The simulation and numerical results show that the proposed AD-FPA-RS scheme not only outperforms the existing HD-FPARS and FD-FPA-RS schemes in terms of outage behavior significantly, but also can obtain full diversity gain without the floor outage performance at high SNR region.

A detailed reinforcement learning framework for resource allocation in non‐orthogonal multiple access enabled‐B5G/6G networks

AbstractThe world of communications technology has recently undergone an extremely significant revolution. This revolution is an immediate consequence of the immersion that the fifth generation B5G and 6G have just brought. The latter responds to the growing need for connectivity and it improves the speeds and qualities of the mobile connection. To improve the energy and spectral efficiency of these types of networks, the non‐orthogonal multiple access (NOMA) technique is seen as the key solution that can accommodate more users and dramatically improve spectrum efficiency. The basic idea of NOMA is to achieve multiple access in the power sector and decode the required signal via continuous interference cancelation. A resource allocation approach is proposed for the B5G/6G‐NOMA network that aims to maximise system throughput, spectrum and energy efficiency and fairness among users while minimising latency. The proposed approach is based on reinforcement learning (RL) with the use of the Q‐Learning algorithm. First, the process of resource allocation as a problem of maximising rewards is formulated. Next, the Q‐Learning algorithm is used to design a resource allocation algorithm based on RL. The results of the simulation confirm that the proposed scheme is feasible and efficient.

Energy-efficient maximization algorithm for energy harvesting under imperfect channel information

In this paper, we propose a novel energy-efficient resource optimization scheme in non-orthogonal multiple access (NOMA) networks with simultaneous wireless information and power transfer (SWIPT). In this system, we consider practical imperfect channel information that accounts for random channel delays and channel estimation errors. Additionally, the small cell users (SCUs) in a heterogeneous network (HetNet) can harvest energy from the small base station (SBS) signal by energy harvesting. Based on the non-linear energy harvesting (NEH) model, the problem of maximizing energy efficiency with imperfect channel state information (CSI) is formulated. Since the formulated problem is a probabilistic mixed non-convex optimization problem, a two-stage algorithm is developed to jointly optimize sub-channel matching and power allocation. In particular, the problem is first transformed into a non-probabilistic problem through the relaxation method. For the sub-channels matching problem, a low-complexity many-to-many matching algorithm is designed to achieve dynamic matching based on the preference lists. For the power allocation problem, the closed-form transmission power of SCUs can be derived by the Dinkelbach method and Lagrangian dual approach. Simulation results show that the proposed scheme can achieve higher energy efficiency than existing linear energy harvesting (LEH)-NOMA and NEH-OFDMA schemes, with improvements of 37.99% and 84.69%, respectively.

Power allocation in NOMA using sum rate-based dwarf mongoose optimization

The increasing number of consumers with diverse data rate needs is leading to increased heterogeneity in traditional cellular networks. Nonorthogonal multiple access (NOMA) has emerged as a promising method to serve a large number of users, but research shows that weak users (WU) and strong users (SU) have different throughputs. Intra-group interference reduces WUs throughput due to the superposition of signals. Improper power distribution impacts NOMA performance and lowers the total system rate. The multi-objective sum rate dwarf mongoose optimization algorithm (M-SRDMOA) is implemented as a solution to the NOMA network power allocation problems. The DMOA approach distributes adequate power to all NOMA users to increase the large sum rate. The effectiveness of the M-SRDMOA approach is supported by existing studies on fair NOMA scheduler (FANS) and multi-objective sum rate-based butterfly optimization algorithm (M-SRBOA). The M-SRDMOA’s potential sum rate with an SNR of 9dB and a noise variation=2 is 14.06 bps/Hz, which is high compared to M-SRBOA and FANS.

Enhanced Energy Transfer Efficiency for IoT-Enabled Cyber-Physical Systems in 6G Edge Networks with WPT-MIMO-NOMA

The integration of wireless power transfer (WPT) with massive multiple-input multiple-output (MIMO) non-orthogonal multiple access (NOMA) networks can provide operational capabilities to energy-constrained Internet of Things (IoT) devices in cyber-physical systems such as smart autonomous vehicles. However, during downlink WPT, co-channel interference (CCI) can limit the energy efficiency (EE) gains in such systems. This paper proposes a user equipment (UE)–base station (BS) connection model to assign each UE to a single BS for WPT to mitigate CCI. An energy-efficient resource allocation scheme is developed that integrates the UE–BS connection approach with joint optimization of power control, time allocation, antenna selection, and subcarrier assignment. The proposed scheme improves EE by 24.72% and 33.76% under perfect and imperfect CSI conditions, respectively, compared to a benchmark scheme without UE–BS connections. The scheme requires fewer BS antennas to maximize EE and the distributed algorithm exhibits fast convergence. Furthermore, UE–BS connections’ impact on EE provided significant gains. Dedicated links improve EE by 24.72% (perfect CSI) and 33.76% (imperfect CSI) over standard connections. Imperfect CSI reduces EE, with the proposed scheme outperforming by 6.97% to 12.75% across error rates. More antennas enhance EE, with improvements of up to 123.12% (conventional MIMO) and 38.14% (massive MIMO) over standard setups. Larger convergence parameters improve convergence, achieving EE gains of 7.09% to 11.31% over the baseline with different convergence rates. The findings validate the effectiveness of the proposed techniques in improving WPT efficiency and EE in wireless-powered MIMO–NOMA networks.

Enhancing wireless communication systems through large intelligent surfaces: a performance analysis of LIS-assisted NOMA networks

The integration of large intelligent surfaces (LIS) with non-orthogonal multiple access (NOMA) networks has emerged as a promising solution to enhance the capacity and coverage of wireless communication systems. In this study, we analyse the performance of a NOMA network with the assistance of LIS. We propose a system model where a base station (BS) equipped with a LIS serves multiple users. The LIS consists of many passive elements that can influence the wireless channel by adjusting the reflection coefficients. We consider a downlink scenario where the BS transmits to multiple users simultaneously using NOMA, and the LIS helps to improve the signal quality and coverage. We additionally evaluate the efficiency of the suggested LIS-assisted NOMA network. In addition, we evaluate the efficiency of the LIS-assisted NOMA network in comparison to conventional NOMA systems that do not utilize LISs. The findings indicate that the LIS has a notable impact on enhancing the system's performance in terms of diversity gain, probability of error, and pairwise error probability (PEP). Moreover, the suggested LIS-assisted NOMA network is shown to be superior to conventional NOMA systems through comparison. These findings offer useful insights into the performance analysis of LIS-assisted NOMA networks. They also serve as inspiration and motivation for future research and development in this new subject, with the potential to revolutionize wireless communication systems.

Secure communication of intelligent reflecting surface-aided NOMA in massive MIMO networks

A Non-Orthogonal Multiple Access (NOMA) network, in which the base station (BS) incorporates massive Multiple-Input Multiple-Output (MIMO) technology, is considered in this paper. This research study focuses on investigating physical layer security in this network when a jammer is present, leveraging intelligent Reflecting Surface (IRS) technology. The IRS is an innovative approach strategically implemented to enhance communication quality by assisting distant users in establishing a reliable connection with the BS. Two key metrics in physical layer security are evaluated: the secrecy rate (SR) for pairs of NOMA users and the secrecy outage probability (SOP). Additionally, the impact of using a jammer is assessed by comparing the network’s performance with and without a jammer. The results indicate that by increasing in the antenna numbers, the rate of secrecy is improved, and the SOP is decreased. Moreover, as the transmit signal-to-noise ratio (SNR) increases, the SR is enhanced, but the SOP is degraded. However, the increase in the IRS element numbers results in a tendency for the SOP to rise. Furthermore, it is evident that incorporating a jammer improves the network’s performance.

Effective capacity of STAR-RIS assisted RSMA network with imperfect SIC

The proliferation of various Internet of Everything applications places urgent demand for high energy efficiency, massive connection and wide coverage for the future communication era. Motivated by this, rate-splitting multiple access (RSMA) and simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) has attracted wide publicity from industry and academia. In this paper, we consider a STAR-RIS assisted two-user RSMA network with imperfect successive interference cancellation, and all channels are modeled as Nakagami-m distribution. By adopting effective capacity (EC) as the metric, we analyze the system performance under certain quality-of-service constraint. Specifically, analytical expressions of EC for a pair of RSMA users are provided. To explore further insights, high signal-to-noise ratio (SNR) conditions are also considered. Furthermore, the effect of some specific elements on system EC performance are analyzed, and some significant conclusions are obtained as follows: (1) As SNR grows, the effective capacities of two users improve, but finally converge to constant at high SNR. (2) The increase in the amount of the STAR-RIS elements can obviously increase the effective capacities. (3) Compared to traditional STAR-RIS assisted non-orthogonal multiple access networks, STAR-RIS assisted RSMA network has distinct advantages to improve system EC performance.

Outage and throughput performance analysis of incremental relaying‐based underlay cognitive nonorthogonal multiple access networks with maximal ratio combining

SummaryIn this paper, we investigate the effectiveness of incremental relaying (IR)‐based underlay cognitive nonorthogonal multiple access (CNOMA) system with maximal ratio combining (MRC). Considering imperfect successive interference cancelation (i‐SIC), we derive analytical expressions for the outage probabilities experienced by the secondary users (SUs) and the system outage probability of the IR‐CNOMA system. We also derive the analytical expression for the outage probability of far SUs by considering IR‐CNOMA system with MRC. The maximum transmit power constraint of the secondary nodes and the interference threshold constraint of the primary receiver are considered in the analysis. We also evaluate the system throughput of IR‐CNOMA network. We also derive outage and throughput expression for the traditional cooperative relaying‐based CNOMA system (CR‐CNOMA) for the purpose of comparison. We derive analytical expression for the asymptotic outage probability and the asymptotic system outage probabilities of the SUs of IR‐CNOMA system. Further, we derive expressions for the optimal power allocation (OPA) factor at the secondary source that minimizes the asymptotic system outage probability of the IR‐CNOMA system. Through numerical and simulation investigations, we demonstrate that the system outage probability significantly lowers when the OPA factor is selected based on the criteria outlined in this work. It can be observed from the results that the IR‐CNOMA system outperforms the conventional CR‐CNOMA system in terms of outage probabilities and throughput. The outage probability is further reduced when IR‐CNOMA system with MRC is considered for the far SUs.

GASBO: User grouping–based gradient average subtraction–based optimisation for NOMA-based fog computing vehicular network

The Internet of Vehicles (IoV) for fog computing (FC) addresses issues such as traffic congestion, transportation efficiency, and privacy. Non-orthogonal multiple access (NOMA) is a popular technology that enhances spectral efficiency and increases the network's access capability. The synchronisation between NOMA and FC radio access networks extends the application of augmented or vehicular networking and other promising uses. However, with the rapid increase in user vehicles and mobile data, the existing IoV has not succeeded in meeting the real-world and dependable communication needs of modern intelligent transportation due to its limited flexibility. To overcome this, we propose a user grouping-based hybrid optimistic framework for resource allocation in NOMA-based FC vehicular networks (FCVR), named the gradient average subtraction-based optimisation (GASBO). Initially, the NOMA-based FCVR is simulated. User grouping is performed based on GASBO using the signal-to-interference-plus-noise ratio and user distance. Finally, resource allocation is achieved using the proposed GASBO, which combines gradient descent optimisation and average subtraction-based optimisation. The analytic measures obtained for energy efficiency, throughput, sub-channel utility, capacity, and penalty function are 5,366,844,362.870 bits/joule, 883.411 Mbps, 82.031, 2316.337, and 0.011, respectively.

Enhancing uplink NOMA cooperative networks with RIS-UAV assistance in Nakagami-[formula omitted] fading channels

Reconfigurable intelligent surfaces (RIS) emerges as a novel communication technology for the 6G networks, boasting advantages such as low cost, high energy efficiency, and wide coverage. To enhance spectrum utilization and ensure signal transmission stability in complex communication scenarios, this paper presents an uplink cooperative non-orthogonal multiple access (NOMA) transmission network assisted by unmanned aerial vehicles (UAV) equipped with RIS. Firstly, a direct link is established between near users and the base station, while a decode-and-forward (DF) relay R and RIS-UAV are deployed between far users and the base station to achieve reliable transmission in a dynamic environment through joint NOMA. Furthermore, an incremental cooperative NOMA scheme is proposed for the uplink transmission, where the relay R remains silent if the RIS-UAV successfully transmits the signal of distant users; if the RIS-UAV fails to transmit the signal to the base station, the relay R is activated to complete the communication between distant users and the base station. Then, the base station employs a selection combining (SC) scheme to process the received signals. Finally, exact expressions of the outage probability under various power allocation strategies are derived. The research results indicate that the outage performance improves with an increase in the number of RIS reflection elements. Moreover, the presence of RIS-UAV can reduce the impact of power allocation strategies on the performance of the uplink NOMA network compared to networks without RIS-UAV.

Implementing green optical waveform system using hybrid cognitive methods for QAM transmission scheme

Abstract This study proposes a hybrid approach combining Energy Detection (ED) and Matched Filter (MF) spectrum sensing techniques to enhance power spectrum density (PSD) in optical Nonorthogonal Multiple Access (NOMA) systems. Optical NOMA has emerged as a key technology for boosting spectral efficiency in optical communication networks. However, optimizing PSD remains a critical challenge due to various factors including signal detection and noise interference. The hybrid ED–MF spectrum sensing method aims to address these challenges by leveraging the strengths of both techniques. Energy Detection (ED) offers simplicity and robustness in detecting primary users, making it suitable for initial spectrum sensing in cognitive radio networks. Matched Filter (MF) spectrum sensing, on the other hand, provides superior signal detection and noise rejection capabilities, particularly in low signal-to-noise ratio (SNR) environments. By integrating these two techniques, we aim to achieve improved sensitivity and accuracy in spectrum sensing, thus enhancing spectral efficiency and system performance in optical NOMA networks. The effectiveness of the proposed hybrid approach is evaluated through theoretical analysis and simulation experiments. Results demonstrate significant enhancements in spectral efficiency and system reliability compared to conventional spectrum sensing methods, highlighting the potential of the hybrid ED–MF approach for enhancing PSD in optical NOMA systems. This research contributes to advancing the design and optimization of optical communication systems for future high-capacity and high-speed data transmission applications. The PSD values −920 are obtained and it confirmed that the proposed algorithm outperforms the standard algorithms.

Optimisation of energy efficiency of ambient backscatter communication and reconfigurable intelligent surfaces in non‐orthogonal multiple access downlink

AbstractThe authors study the energy efficiency (EE) of ambient backscatter communication (AmBC) device‐assisted and reconfigurable intelligent surfaces (RIS)‐assisted non‐orthogonal multiple access (NOMA) downlinks. The authors establish two optimisation problems based on the two collaborative devices (AmBC devices, RIS) with the objective of maximising the EE of the system, taking into account the requirements of power limitation and rate limitation, etc. and also obtain the solutions of two problems by optimising the relevant performance metrics based on the alternating optimisation algorithm. For the backscatter device (BD)‐aided downlink NOMA network, the problem is first decoupled into three subproblems, where the power allocation optimisation subproblem is solved by using the quadratic transformation method and the subgradient algorithm. The maximum EE is obtained by iterating according to the Dinkelbach's algorithm. For the RIS‐aided downlink NOMA network, the power allocation problem is solved by the same method as above and the phase optimisation problem is solved by the successive convex approximation method. Numerical results show that the proposed algorithm can achieve convergence after several iterations, and the EE of systems with BD‐assisted and RIS‐assisted have different levels of sensitivity to different influencing factors.

Enhancing NOMA Network Security with RIS-UAV Integration: Exploring PPO Technique

In order to improve the security aspects of a nonorthogonal multiple access (NOMA) downlink network, we investigate the use of the proximal policy optimization (PPO) technique in this study. This network is uniquely augmented with reconfi- gurable intelligent surfaces (RIS) mounted on unmanned aerial vehicles (UAVs). The main objective of this article is to prevent possible eavesdroppers from accessing the network while still assuring continuous and secure connectivity for legitimate users. The network configuration includes a UAV outfitted with a RIS, which plays an important role in signal propagation. This work aims to increase the secrecy rates of all user communications in eavesdropping prone locations. By adaptively modifying the phase shifts and power distributions through the RIS the proposed PPO algorithm not only shows adaptability and effectiveness in securing wireless communications, but also highlights the significant advances made in communication system security through this technology.

Sum-rate maximization for a distributed space-time block code-aided cooperative NOMA with energy harvesting

AbstractIn this paper, we exploit the spatial and transmission diversities in cooperative non-orthogonal multiple access (C-NOMA) networks to improve the system sum-rate. To achieve this, we propose a user-pairing scheme where near-field user pairs serve as relays for user pairs in the far-field region. Based on this pairing scheme, we incorporate a space-time block code transmission technique at the near-field user pairs to maximize the transmission diversity in the cooperative phase. Moreover, we consider a non-linear energy harvesting model at the near-field user pair to alleviate the problem of energy consumption during the cooperative transmission phase. Further to this, we formulate a sum-rate maximization problem that is addressed from the viewpoint of joint power allocation factor and power splitting ratio optimization. We develop a low-computational iterative algorithm based on the concepts of the Stackelberg game and the Nash bargaining solution. We benchmark our findings with different scenarios, such as energy harvesting C-NOMA with a fixed power allocation factor and power splitting ratio, energy harvesting C-NOMA without STBC, non-cooperative NOMA, and orthogonal multiple access. The results obtained via simulations outperform the benchmark schemes.

A Self-Supervised GCN Model for Link Scheduling in Downlink NOMA Networks

INTRODUCTION: Downlink Non-Orthogonal Multiple Access (NOMA) networks pose challenges in optimizing power allocation efficiency due to their complex design.OBJECTIVES: This paper aims to propose a novel scheme utilizing Graph Neural Networks to address the optimization challenges in downlink NOMA networks.METHODS: We transform the optimization problem into an optimal link scheduling problem by modeling the network as a bipartite graph. Leveraging Graph Convolutional Networks, we employ self-supervised learning to learn the optimal link scheduling strategy.RESULTS: Simulation results showcase a significant enhancement in power allocation efficiency in downlink NOMA networks, evidenced by notable improvements in both average accuracy and generalization ability. CONCLUSION: Our proposed scheme demonstrates promising potential in substantially augmenting power allocation efficiency within downlink NOMA networks, offering a promising avenue for further research and application in wireless communications.