Downlink Non-orthogonal Multiple Access Network Research Articles

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.

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.

Power allocation scheme for sum rate and fairness trade-off in downlink NOMA networks

Non-orthogonal multiple access (NOMA) is an essential enabler technology that is expected to help satisfy the key requirements of increased system throughput in future wireless networks. However, another equally important aspect that should go hand-in-hand with system throughput is user fairness for any network. But, to the best of our knowledge, even though there have been works that look at system throughput or user fairness maximization for NOMA-based networks, they looked at these as a single objective optimization problem, where one is the objective and the other is one of the constraints. However, quite often, joint optimization of both system throughput and user fairness is required to make optimized decisions in the face of trade-offs between these two equally important but conflicting objectives. In this regard, this paper formulates a multi-objective optimization problem to jointly maximize the sum rate and user fairness in a downlink transmission NOMA system, through optimize power allocation (PA), under system-imposed constraints. A weighted sum approach is used to turn the multi-objective optimization problem into a single-objective optimization problem to make it analytically tractable. The optimized PA is then obtained using Lagrange dual decomposition method and Karush–Kuhn–Tucker (KKT) conditions. Using our derived expressions, we propose an iterative PA algorithm that converges fast enough to be employed in practical NOMA networks. We also present simulation results to highlight the effectiveness of the proposed solution. Further, the performance of the proposed method is compared with that of the benchmark methods.

Physical layer security analysis of IRS-based downlink and uplink NOMA networks

In recent years, the development of intelligent reflecting surface (IRS) in wireless communications has enabled control of radio waves to reduce the detrimental impacts of natural wireless propagation. These can achieve significant spectrum and energy efficiency in wireless networks. Non-orthogonal multiple access (NOMA) technology, on the other hand, is predicted to improve the spectrum efficiency of fifth-generation and later wireless networks. Motivated by this reality, we consider the IRS-based NOMA network in the downlink and uplink scenario with a pernicious eavesdropper. Moreover, we investigated the physical layer security (PLS) of the proposed system by invoking the connection outage probability (COP), secrecy outage probability (SOP), and average secrecy rate (ASR) with analytical derivations. The simulation results reveal that (i) it is carried out to validate the analytical formulas, (ii) the number of meta-surfaces in IRS, transmit power at the base station, and power allocation parameters all play an essential role in improving the system performance, and (iii) it demonstrates the superiority of NOMA to the traditional orthogonal multiple access (OMA).

Joint Phase Shift and Beamforming Design in a Multi-User MISO STAR-RIS Assisted Downlink NOMA Network

Simultaneous transmitting and reflecting reconfigurable intelligent surfaces (STAR-RIS) has gradually been considered as a promising technology in the wireless communication networks. Besides, non-orthogonal multiple access (NOMA) is also the key technology in the sixth-generation (6 G) wireless communication system. In this work, we study a multiple input single output (MISO) STAR-RIS assisted NOMA downlink network and investigate the energy efficiency (EE) maximization to achieve the tradeoff between the sum rate and the power consumption. The original formulated problem is non-convex due to the coupled beamforming vectors of the users and phase shifts of the STAR-RIS. To efficiently solve the problem, we split the original non-convex problem into the phase shift and beamforming optimization problems and then solve them alternatively. In the phase shift optimization, fractional programming (FP) is applied to transform the sum rate maximum problem to convex semidefinite relaxation (SDR) one with the rank-one constraint. After this, a novel sequential rank-one constraint relaxation (SROCR) is proposed to convert the rank-one constraint into a convex one, which can effectively overcome the inadequacy of Gaussian randomization, i.e., quality of the solutions and computational complexity. Similarly, FP is applied to solve the beamforming problem by transforming it to SDR problem. It turns out that the optimal solution of the SDR beamforming optimization problem can be guaranteed to be rank-one by the mathematical proof and experiments. The simulation results demonstrate the STAR-RIS NOMA system can achieve the superior performance in EE.

Performance of CDRT-Based Underlay Downlink NOMA Network With Combining at the Users

The performance of an underlay coordinated direct and relay transmission (CDRT) based non-orthogonal multiple access (NOMA) network is limited by the random nature of the transmit powers due to the interference temperature limit (ITL) imposed by the primary network. In this paper, we show that combining the signals at both near and far users can significantly enhance throughput. Considering the practical scenario of imperfect successive interference cancellation, the performance of near and far user nodes is analyzed in terms of throughput and outage probability. The traditional case of static ITL is considered first. Then, analysis is presented for the case when the ITL depends on the primary channel state information, and it is shown that the gain in performance can be very large over static ITL. Closed-form expressions for NOMA power apportioning are presented for a special case. Further, it is shown that how optimum parameters can be chosen to maximize the performance. Simulations validate the derived analytical expressions.

FD-NOMA Enabled Multiuser Transmission With Backscatter Communication

This letter investigates a full-duplex (FD) non-orthogonal multiple access (NOMA) enabled multiuser transmission with backscatter communication (FD-MTBC), where a multiuser downlink NOMA network is served by an FD source while backscatter devices transmit their information to the source simultaneously. Considering the constraints for successive interference cancellation (SIC) and the desired target uplink sum rate, we formulate an optimization problem to maximize the downlink sum rate. Further, we propose an iterative algorithm that jointly optimizes the power allocation coefficient and reflection coefficient to maximize the downlink sum rate. The effectiveness of the proposed algorithm is demonstrated using simulation results.

STAR-IOS Aided NOMA Networks: Channel Model Approximation and Performance Analysis

Compared with the conventional reconfigurable intelligent surfaces (RIS), simultaneous transmitting and reflecting intelligent omini-surfaces (STAR-IOSs) are able to achieve 360° coverage “smart radio environments”. By splitting the energy or altering the active number of STAR-IOS elements, STAR-IOSs provide high flexibility of successive interference cancellation (SIC) orders for non-orthogonal multiple access (NOMA) systems. Based on the aforementioned advantages, this paper investigates a STAR-IOS-aided downlink NOMA network with randomly deployed users. We first propose three tractable channel models for different application scenarios, namely the central limit model, the curve fitting model, and the M-fold convolution model. More specifically, the central limit model fits the scenarios with large-size STAR-IOSs while the curve fitting model is extended to evaluate multi-cell networks. However, these two models cannot obtain accurate diversity orders. Hence, we figure out the M-fold convolution model to derive accurate diversity orders. We consider three protocols for STAR-IOSs, namely, the energy splitting (ES) protocol, the time switching (TS) protocol, and the mode switching (MS) protocol. Based on the ES protocol, we derive closed-form analytical expressions of outage probabilities for the paired NOMA users by the central limit model and the curve fitting model. Based on three STAR-IOS protocols, we derive the diversity gains of NOMA users by the M-fold convolution model. The analytical results reveal that the diversity gain of NOMA users is equal to the active number of STAR-IOS elements. Numerical results indicate that 1) in high signal-to-noise ratio regions, the central limit model performs as an upper bound of the simulation results, while a lower bound is obtained by the curve fitting model; 2) the TS protocol has the best performance but requesting more time blocks than other protocols; 3) the ES protocol outperforms the MS protocol as the ES protocol has higher diversity gains.

Performance analysis for reconfigurable intelligent surface assisted downlink NOMA networks

In this paper, a reconfigurable intelligent surface (RIS) assisted downlink non-orthogonal multiple access (NOMA) network is considered, where a base station communicates with a pair of users with the assistance of a RIS. The performance of RIS-assisted downlink NOMA networks is investigated by exploiting the coherent phase shifting design. In particular, the central limit theorem based Gaussian approximation is introduced to model the sum of independent and identically distributed random variables and derive the approximate expressions of the outage probability for two users. Furthermore, the upper bounds for the outage probability are obtained based on the property of the Bessel function. Additionally, both the asymptotic outage probabilities and the asymptotic upper bounds at high signal-to-noise ratio are derived and the diversity order achieved by the network is obtained. Simulation results are provided to validate the theoretical findings and demonstrate that RIS-NOMA can achieve superior outage performance compared to RIS-assisted orthogonal multiple access and conventional full-duplex decode-and-forward relaying schemes. Moreover, it can be observed that the outage performance of RIS-NOMA can be tremendously enhanced with increasing the number of reflecting elements.

Joint Adaptive M-QAM Modulation and Power Adaptation for a Downlink NOMA Network

In this paper, we study joint adaptive M-QAM modulation and power adaptation for a downlink two-user non-orthogonal multiple access (NOMA) network. Without sacrificing bit error rate (BER), joint adaptive transmission can fully utilize the time-varying nature of wireless channels, by allowing both power and rate to adapt to channel fading. Two adaptive power allocation strategies, namely, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Scheme 1</i> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Scheme 2</i> , each of which guarantees the minimum target rate for one user while supporting the highest possible rate for the other, are first proposed. Then, based on the two power schemes, the performance of joint adaptive transmission in terms of average spectral efficiency (SE) is studied for continuous-rate and discrete-rate modulation, while guaranteeing the minimum required rate and BER requirements. With the focus on practical discrete-rate M-QAM modulation, it is proved that for the strong user in <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Scheme 1</i> and the weak user in <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Scheme 2</i> , their average SEs converge to the minimum target rates. In order to further increase the total transmission rate, we then propose a dynamic rate and power adaptation (DRPA) algorithm, aiming to increase the rate of one user without sacrificing the rate of the other. It is shown that at high SNRs, the DRPA algorithm allows the strong user in <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Scheme 1</i> and the weak user in <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Scheme 2</i> to continue to increase their transmission rates until reaching the highest modulation order that the system can support. Hence, the total transmission rate can be greatly increased at high SNRs due to the adoption of DRPA, by allowing both users in each scheme to reach the highest transmission rate in the system.

Analysis of user pairing non-orthogonal multiple access network using deep Q-network algorithm for defense applications

Non-orthogonal multiple access (NOMA) networks play an important role in defense communication scenarios. Deep learning (DL)-based solutions are being considered as viable ways to solve the issues in fifth-generation (5G) and beyond 5G (B5G) wireless networks, since they can provide a more realistic solution in the real-world wireless environment. In this work, we consider the deep Q-Network (DQN) algorithm-based user pairing downlink (D/L) NOMA network. We have applied the convex optimization (CO) technique and optimized the sum rate of all the wireless users. First, the near-far (N-F) pairing and near-near and far-far (N-N and F-F) pairing strategies are investigated for the multiple numbers of users, and a closed-form (CF) expression of the achievable rate is derived. After that, the optimal power allocation (OPA) factors are derived using the CO technique. Through simulations, it has been demonstrated that the DQN algorithms perform much better than the deep reinforcement learning (DRL) and conventional orthogonal frequency-division multiple access (OFDMA) schemes. The sum-rate performance significantly increases with OPA factors. The simulation results are in close agreement with the analytical results.

Sum Rate Maximization-based Fair Power Allocation in Downlink NOMA Networks

Non-orthogonal multiple access (NOMA) has been seen as a promising technology for 5G communication. The performance optimization of NOMA systems depends on both power allocation (PA) and user pairing (UP). Most existing researches provide sub-optimal solutions with high computational complexity for PA problem and mainly focuses on maximizing the sum rate (capacity) without considering the fairness performance. Also, the joint optimization of PA and UP needs an exhaustive search. The main contribution of this paper is the proposing of a novel capacity maximization-based fair power allocation (CMFPA) with low-complexity in downlink NOMA. Extensive investigation and analysis of the joint impact of signal to noise ratio (SNR) per subcarrier and the channel gains of the paired users on the performance of NOMA in terms of the capacity and the user fairness is presented. Next, a closed-form equation for the power allocation coefficient of CMFPA as a function of SNR, and the channel gains of the paired users is provided. In addition, to jointly optimize UP and PA in NOMA systems an efficient low-complexity UP (ELCUP) method is proposed to be incorporated with the proposed CMFPA to compromise the proposed joint resource allocation (JRA). Simulation results demonstrate that the proposed CMFPA can improve the capacity and fairness performance of existing UP methods, such as conventional UP, and random UP methods. Furthermore, the simulation results show that the proposed JRA significantly outperforms the existing schemes and gives a near-optimal performance.

Resource Allocation Based on User Pairing and Subcarrier Matching for Downlink Non-Orthogonal Multiple Access Networks

The traditional orthogonal multiple access (OMA) is unable to satisfy the needs of large number of smart devices. To increase the transmission rate in the limited spectrum resource, implementation of both non-orthogonal multiple access (NOMA) and successive interference cancelation (SIC) is essential. In this paper, an optimal resource allocation algorithm in NOMA is proposed to maximize the total system rate in a multi-sector multi-subcarrier relay-assisted communication network. Since the original problem is a non-convex problem with mixed integer programming which is non-deterministic polynomial-time (NP)-hard, a three-step solution is proposed to solve the primal problem. Firstly, we determine the optimal power allocation of the outer users by using the approach of monotonic discrimination, and then the optimal user pairing is determined. Secondly, the successive convex approximation (SCA) method is introduced to transform the non-convex problem involving central users into convex one, and the Lagrangian dual method is used to determine the optimal solution. Finally, the standard Hungarian algorithm is utilized to determine the optimal subcarrier matching. The simulation results show that resource allocation algorithm is able to meet the user performance requirements with NOMA, and the total system rate is improved compared to the existing algorithms.

Capacity and Fairness Maximization-Based Resource Allocation for Downlink NOMA Networks

Non-orthogonal multiple access (NOMA) is one of the leading technologies for 5G communication. User pairing (UP) and power allocation (PA) are the key controlling mechanisms for the optimization of the performance of NOMA systems. This paper presents a novel UP and PA (UPPA) technique for capacity and fairness maximization in NOMA called (CFM-UPPA). The impact of the power allocation coefficient and the ratio between the channel gains of the paired users on the sum-rate capacity and the fairness in NOMA is firstly investigated. Then, based on this investigation, the PA and UP algorithms of the CFM-UPPA technique are proposed. The power allocation coefficient of the proposed PA is formulated as an exponentially decaying function of the ratio between the channel gains of the paired users to maximize the capacity and the fairness, and its maximum value is adjusted to guarantee the successive interference cancellation (SIC) constraints. The proposed UP is based on selecting the user that has the highest channel gain per subcarrier as the strong user to maximize the capacity and selecting the user that has the closest lower channel gain to the strong user’s channel gain as the weak user to improve the fairness and capacity. The performance evaluation of the proposed CFM-UPPA technique in terms of capacity, fairness, and outage probability demonstrates that its performance significantly outperforms that of the orthogonal multiple access (OMA) system and that of the NOMA system with random UP. Also, the simulation results demonstrate the efficiency of the proposed PA in improving the performance of other UP algorithms, such as the random UP algorithm.

Reconfigurable Intelligent Surface Assisted Coordinated Multipoint in Downlink NOMA Networks

In this letter, we investigate the amalgamation between the reconfigurable intelligent surface (RIS) technology and the joint transmission coordinated multipoint (JT-CoMP) in order to enhance the performance of a cell-edge user equipment (UE) in a two-user non-orthogonal multiple access (NOMA) group without deteriorating the performance of the NOMA cell-center UE. The RIS is adopted to construct a strong combined channel gain at the cell-edge UE, while JT-CoMP is used to mitigate the effects of inter-cell interference (ICI). In this proposed framework, we derive first a closed-form expression for the ergodic rate of the cell-edge UE, and then we evaluate the network spectral efficiency. We validate the derived expression through Monte-Carlo simulations, where we demonstrate the efficacy of the proposed framework compared to other multiple access techniques proposed in the literature.

Down-Link NOMA Networks in the Presence of IQI and Imperfect SIC: Receiver Design and Performance Analysis

This article addresses the practical aspects that may affect the performance of down-link non-orthogonal multiple access (NOMA) systems. The system performance of two down-link NOMA users, where both users suffer from the effects of in-phase/quadrature-phase imbalance (IQI), while the first user also experiences imperfect successive interference cancellation (SIC) is examined. In order to mitigate the effects of IQI, an optimal maximum likelihood (ML) receiver is designed and analyzed, and the performance of the proposed receiver is compared with the traditional ML one. Moreover, closed-form mathematical expressions of the conditional pairwise error probability (PEP) for each user are derived. The simulation results validate the analysis and demonstrate that the proposed receiver outperforms the traditional one, with the ability to reduce the effects of IQI for both users.

Bit Error Rate for NOMA Network

This letter examines the bit error rate (BER) performance of downlink non-orthogonal multiple access networks for binary phase-shift keying modulation. Exact BER expression is derived for each user in closed-form under additive white Gaussian noise and Rayleigh fading channels in perfect and imperfect successive interference cancellation (SIC) cases. Next, in perfect SIC case, the asymptotic BER expression in a high signal-to-noise ratio (SNR) region is obtained to express the behavior of the network with diversity and array gains. On the other hand, in imperfect SIC case, the upper bound for BER is attained, and at high SNR values, the BER reveals an error floor, and hence a zero diversity gain is achieved. Then, a feasible range of power allocation coefficients is found such that a good BER performance can be provided for each user. Finally, through simulations and software-defined radio-based real-time tests, analytical results are validated.

Performance analysis and SINR‐based power allocation strategies for downlink NOMA networks

This study analyses the performance of downlink non-orthogonal multiple-access (NOMA) networks over independent but not necessarily identically distributed Rayleigh fading channels by deriving closed-form expressions for the average signal-to-interference-plus-noise ratio (SINR), average achievable rate, and outage probability of all network users. Moreover, SINR-based power allocation strategies are studied. Specifically, the optimisation problems of max–min SINR, multi-objective SINR, sum-SINR and proportional-fairness-SINR maximisation under minimum SINR constraints are formulated and shown to be non-convex. Additionally, the problems of total power and sum-SINR minimisation are also formulated. Particularly, the formulated problems take the form of linear-fractional programming problems. By applying intelligent reformulation techniques, these problems have been reformulated into convex optimisation problems, and thus efficiently solved. Numerical evaluations are presented to validate the derived closed-form expressions for the different performance metrics, which are found to be in agreement with the network simulation results. More importantly, it has been demonstrated that the user with the best channel conditions achieves full diversity order, whereas all the other users achieve diversity orders equivalent to their ordered channel conditions. Finally, the reformulated power allocation strategies are evaluated, and shown to coincide with the original problem formulations.

Distributed Rate Control in Downlink NOMA Networks With Reliability Constraints

Non-orthogonal multiple access (NOMA) has been identified as a promising technology for future wireless systems due to its performance gains in spectral efficiency when compared to conventional orthogonal schemes (OMA). This gain can be easily translated to an increasing number of served users, but imposes a challenge in the system reliability which is of vital importance for new services and applications of coming cellular systems. To cope with these issues we propose a NOMA rate control strategy that makes use only of topological characteristics of the scenario and the reliability constraint. We attain the necessary conditions so that NOMA overcomes the OMA alternative, while we discuss the optimum allocation strategies for the 2-user NOMA setup when operating with equal rate or maximum sum-rate goals. In such scenario we show that the user with the largest target error probability times the ratio between the average receive signal power and the average interference power, should be scheduled to be decoded first for optimum performance. We compare numerically the performance of our allocation scheme with its ideal counterpart requiring full CSI at the BSs and infinitely long blocklength, and show how the gap increases as the reliability constraint becomes more stringent. Results also evidence the benefits of NOMA when the co-interference can be efficiently canceled, specially when the goal is to maximize the sum-rate.

Joint Spectral and Energy Efficiency Optimization for Downlink NOMA Networks

Non-orthogonal multiple access (NOMA) holds the promise to be a key enabler of 5G communication. However, the existing design of NOMA systems must be optimized to achieve maximum rate while using minimum transmit power. To do so, this paper provides a novel technique based on multi-objective optimization to efficiently allocate resources in the multi-user NOMA systems supporting downlink transmission. Specifically, our unique optimization technique jointly improves spectrum and energy efficiency while satisfying the constraints on users quality of services (QoS) requirements, transmit power budget and successive interference cancellation. We first formulate a joint problem for spectrum and energy optimization and then employ dual decomposition technique to obtain an efficient solution. For the sake of comparison, a low complexity single-objective NOMA optimization scheme is also provided as a benchmark scheme. The simulation results show that the proposed joint approach not only performs better than the traditional benchmark NOMA scheme but also significantly outperforms its counterpart orthogonal multiple access (OMA) scheme in terms of both energy and spectral efficiency.