Downlink Non-orthogonal Multiple Access Research Articles

Cluster-Based Strategy for Maximizing the Sum-Rate of a Distributed Reconfigurable Intelligent Surface (RIS)-Assisted Coordinated Multi-Point Non-Orthogonal Multiple-Access (CoMP-NOMA) System.

This article proposes a distributed intelligent Coordinated Multi-Point Non-Orthogonal Multiple-Access (CoMP-NOMA) collaborative transmission model with the assistance of reconfigurable intelligent surfaces (RISs) to address the issues of poor communication quality, low fairness, and high system power consumption for edge users in multi-cellular networks. By analyzing the interaction mechanisms and influencing factors among RIS signal enhancement, NOMA user scheduling, and multi-point collaborative transmission, the model establishes RIS-enhanced edge user grouping and coordinates NOMA user clusters based on this. In the multi-cell RIS-assisted JT-CoMP NOMA downlink transmission, joint optimization of the power allocation (PA), user clustering (UC), and RIS phase-shift matrix design (PS) poses a challenging Mixed-Integer Non-Linear Programming (MINLP) problem. The original problem is decomposed by optimizing the formulas into joint sub-problems of PA, UC, and PA and PS, and solved using an alternating optimization approach. Simulation results demonstrate that the proposed scheme effectively reduces the system's power consumption while significantly improving the system's throughput and rates.

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.

Optimal Decoding Order and Power Allocation for Sum Throughput Maximization in Downlink NOMA Systems.

In this paper, we consider a downlink non-orthogonal multiple access (NOMA) system over Nakagami-m channels. The single-antenna base station serves two single-antenna NOMA users based on statistical channel state information (CSI). We derive the closed-form expression of the exact outage probability under a given decoding order, and we also deduce the asymptotic outage probability and diversity order in a high-SNR regime. Then, we analyze all the possible power allocation ranges and theoretically prove the optimal power allocation range under the corresponding decoding order. The demarcation points of the optimal power allocation ranges are affected by target data rates and total power, without an effect from the CSI. In particular, the values of the demarcation points are proportional to the total power. Furthermore, we formulate a joint decoding order and power allocation optimization problem to maximize the sum throughput, which is solved by efficiently searching in our obtained optimal power allocation ranges. Finally, Monte Carlo simulations are conducted to confirm the accuracy of our derived exact outage probability. Numerical results show the accuracy of our deduced demarcation points of the optimal power allocation ranges. And the optimal decoding order is not constant at different total transmit power levels.

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.

Joint subchannel power allocation for downlink NOMA systems based on quantum carnivorous plant algorithm

Currently, most existing research on non-orthogonal multiple access (NOMA) systems converts power allocation into two independent procedures, i.e., inter-subchannel power allocation and intra-subchannel power allocation. However, improper inter-subchannel power allocation will adversely affect the power allocation process of intra-subchannel. If the power allocations of inter-subchannel and intra-subchannel are optimized simultaneously, it usually needs high computational complexity, and is hard to obtain an optimal solution. To tackle this issue, this paper studies the joint subchannel power allocation for NOMA systems and proposes a new intelligent algorithm called quantum carnivorous plant algorithm (QCPA) for simultaneously optimizing inter-subchannel and intra-subchannel power allocations. Analysis of the convergence of QCPA verified its superior performance on the test functions. By utilizing the optimal solution obtained by QCPA as the power allocation scheme, energy efficiency and sum transmission rate in NOMA systems are significantly increased compared to existing traditional power allocation methods. The results above demonstrate that QCPA effectively addresses test functions and the power allocation problem for NOMA. QCPA possesses favorable convergence in comparison to other comparison algorithms and methods.

Queueing Theoretic Models for Multiuser MISO Content-Centric Networks With SDMA, NOMA, OMA and Rate-Splitting Downlink

Queueing Theoretic Models for Multiuser MISO Content-Centric Networks With SDMA, NOMA, OMA and Rate-Splitting Downlink

Dynamic resource allocation for energy-efficient downlink NOMA systems in 5G networks

Non-Orthogonal Multiple Access (NOMA) is a promising energy-efficient technology designed to satisfy the demands of future networks by efficiently sharing radio resources. In NOMA, the same radio resource is simultaneously assigned to two users at different power levels based on the NOMA-power domain. Resource allocation in NOMA presents a non-convex challenge, characterized as a non-deterministic polynomial (NP-hard) problem. This involves user and channel assignment and power allocation, making it an extraordinarily complex task to achieve an optimal solution. In this work, Simulated Annealing (SA) is proposed as an optimization technique for resource allocation in an energy-efficient downlink NOMA system. This resource allocation scheme addresses user and channel assignment, as well as power allocation, using SA as an efficient standalone approach to maximize energy efficiency in NOMA. SA is utilized to execute the assignment of users to channels, distribute the necessary power for each channel, and determine the power ratio among users sharing the same channel. The results obtained demonstrate a significant improvement in energy efficiency, outperforming the existing numerical methods by 22 %. The proposed SA scheme not only achieves a close optimal solution but also in less computational time, offering sufficient reliability in terms of energy efficiency enhancement when compared to the existing numerical method.

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.

Energy-efficient UAV communication: A NOMA scheme with resource allocation and trajectory optimization.

This work investigates a downlink nonorthogonal multiple access (NOMA) scheme with unmanned aerial vehicle (UAV) aided wireless communication, where a single UAV was regarded as an air base station (ABS) to communicate with multiple ground users. Considering the constraints of velocity and maneuverability, a UAV energy efficiency (EE) model was proposed via collaborative design resource allocation and trajectory optimization. Based on this, an EE maximization problem was formulated to jointly optimize the transmit power of ground users and the trajectory of the UAV. To obtain the optimal solutions, this nonconvex problem was transformed into an equivalent convex optimization problem on the basis of three user clustering algorithms. After several alternating iterations, our proposed algorithms converged quickly. The simulation results show an enhancement in EE with NOMA because our proposed algorithm is nearly 99.6% superior to other OMA schemes.

High-Speed Power Allocation in NOMA System Using FPGA-Based DNN

Artificial Intelligence (AI) is rapidly transforming the healthcare, finance and transportation industries. This paper presents a field-programmable gate array (FPGA)-based neural network accelerator (NNA) design for power allocation in downlink nonorthogonal multiple access (NOMA) networks. The proposed hardware accelerator effectively cuts computational costs while delivering performance on par with the highest sum capacity. Numerical results show that this NNA offers a remarkable computational speed increase of up to 99% compared to the conventional exhaustive search method. Furthermore, the deep learning (DL) model achieved high accuracy (0.92 training, 0.93 testing), and the hardware accelerator design for this DL inference model was implemented on the PYNQ-Z2 board-constrained edge device to predict power allocation coefficients in NOMA systems.

Characterization and Optimization of Coding Performance in Downlink NOMA With Finite-Alphabet Inputs and Finite Blocklength

Characterization and Optimization of Coding Performance in Downlink NOMA With Finite-Alphabet Inputs and Finite Blocklength

On performance analysis of non-orthogonal multiple access downlink for cellular-connected unmanned aerial vehicle relaying assisted vehicle-to-everything system

This paper presents the unmanned aerial vehicle (UAV) relays’ assisted vehicle-to-everything (V2X) network to implement the internet of things (IoT) systems with improvement in the coverage area. Such a network benefits from many advantages of the non-orthogonal multiple access (NOMA) scheme. We have implemented a decode-and-forward (DF) scheme for these UAVs. Then, we characterize the channels as Nakagami-m fading to evaluate the performance of the system. We derive closed-form expressions of outage probability (OP), ergodic capacity (EC), and throughput. The results show that the performance of the system depends on the transmitted signal-to-noise ratio (SNR) at the base station and the heights of the UAV relays. Target rate and power allocation factors are two main parameters that can be adjusted to achieve better performance. The results also compare to the system without UAV and OMA technique that shows the advantages of deploying UAV-assisted NOMA. Therefore, the design of NOMA for UAV relay-assisted V2X systems provides sufficient demand. The simulation results verified the effectiveness of the proposed UAV network and the precision of the theoretical analysis.

Covert performance enhancement in NOMA enabled CoMP network with optimal RIS selection

In this paper, we consider the covert rate maximization problem for the cell edge user in a reconfigurable intelligent surface (RIS) aided downlink non-orthogonal multiple access (NOMA) network with coordinated multipoint (CoMP) transmission in the presence of channel estimation errors. We derive the analytical expression for the detection error probability (DEP) at the adversary (Willie) assuming the worst case scenario where they employ optimal detection threshold. With the derived analytical expression, we propose an optimal RIS selection scheme to boost the covert rate. To further improve the covert performance, we optimize the NOMA power allocation coefficients and phase shifts of the selected RIS subject to the target rate and covertness constraints. Simulation results demonstrate the improvement in covert rate and robustness offered by the proposed scheme in the presence of channel estimation errors over other benchmarks.

Closed-form BER expression for multi-user downlink NOMA

Massive machine-type communication (MMTC) is an essential element for realizing the Internet of Things (IoT). However, certain challenges arise because MMTC should support a massive number of users. Recently, non-orthogonal multiple access (NOMA) has been highlighted as a technology for MMTC in a limited frequency band. To design and operate a NOMA-based communication system for a massive number of users, an accurate performance analysis for an arbitrary number of users and a practical power assignment method for the channel condition of each user are required. In this study, the exact bit error rate (BER) expression for an arbitrary user number is derived in an explicit closed form for NOMA-based communication. In addition, for analytical purposes, an approximate expression with high accuracy is proposed. To achieve an extension to the fading channel, the average BER expressions for the Rayleigh and Nakagami-m fading channels are presented in closed forms. Based on the derived BER expression, a power assignment algorithm that can achieve the target performance is proposed when each user is associated with a different signal-to-noise ratio. The derived BER expressions and the power assignment algorithm were verified based on computer simulations.

Subcarrier-users nomination process for downlink NOMA system

The non-orthogonal multiple access (NOMA) characteristics of 5G radio access allow for more efficient resource distribution. NOMA improves spectral efficiency by allowing Power domain users to transmit power concurrently with other users of time and spectrum resources. The selection of the subcarrier and the nomination of users to the subcarrier is of the utmost importance to maximize spectral efficiency fairness among the users and improve the data rate of weak users in the downlink NOMA system. The least gain subcarrier First-threshold-based Adaptive user grouping algorithm (LGSF-TBAUGA) has been devised for this purpose. This algorithm maintains a significant channel gain differential based on a threshold, thus avoiding successive interference cancellation (SIC) process imperfections. The computational complexity of the proposed technique is calculated and compared to other approaches. The power coefficients of the selected users are used to allocate power to them. The proposed method improves the weak user data and overall system sum rates. As a result, the spectrum efficiency and user fairness index have been greatly enhanced compared to some existing algorithms.

On the Performance of Noma Systems with Different User Grouping Strategies

This paper investigates several critical issues on the ergodic sum capacity and system outage performance of downlink non-orthogonal multiple access (NOMA) systems with different numbers of users per cluster sharing the same resource. The outcomes from this work suggest that NOMA systems with more users per cluster perform better under a low channel gain, while those with fewer users per cluster perform better under a high channel gain. It discloses a fact that a traditional NOMA system with a fixed user grouping scheme may not be a good choice to deal with complex channel conditions with diverse applications. To address the issue, this paper introduces a concept of mixed user grouping NOMA, which outperforms OMA and traditional NOMA significantly. The work in this paper lays a foundation for more further investigations on mixed user grouping NOMA systems.

Novel Channel Aware Power Control for a Multi-User Downlink NOMA Network

Novel Channel Aware Power Control for a Multi-User Downlink NOMA Network

Secure 5G downlink NOMA cognitive relay network: joint the impact of imperfect spectrum sensing and outdated CSI

Secure 5G downlink NOMA cognitive relay network: joint the impact of imperfect spectrum sensing and outdated CSI

Secure User Pairing and Power Allocation for Downlink Non-Orthogonal Multiple Access against External Eavesdropping.

We propose a secure user pairing (UP) and power allocation (PA) strategy for a downlink Non-Orthogonal Multiple Access (NOMA) system when there exists an external eavesdropper. The secure transmission of data through the downlink is constructed to optimize both UP and PA. This optimization aims to maximize the achievable sum secrecy rate (ASSR) while adhering to a limit on the rate for each user. However, this poses a challenge as it involves a mixed integer nonlinear programming (MINLP) problem, which cannot be efficiently solved through direct search methods due to its complexity. To handle this gracefully, we first divide the original problem into two smaller issues, i.e., an optimal PA problem for two paired users and an optimal UP problem. Next, we obtain the closed-form optimal solution for PA between two users and UP in a simplified NOMA system involving four users. Finally, the result is extended to a general 2K-user NOMA system. The proposed UP and PA method satisfies the minimum rate constraints with an optimal ASSR as shown theoretically and as validated by numerical simulations. According to the results, the proposed method outperforms random UP and that in a standard OMA system in terms of the ASSR and the average ASSR. It is also interesting to find that increasing the number of user pairs will bring more performance gain in terms of the average ASSR.

A streamlined user grouping in downlink NOMA systems

AbstractReducing SIC operations and interference while maintaining the same radio resources for users in a cluster is a potential research direction in non‐orthogonal multiple access (NOMA) systems. In order to reach this goal, a streamlined user grouping is proposed for a four‐user cluster in downlink NOMA systems, which is carried out based on the in‐phase and quadrature components of a constellation. In terms of bit error rate performance, the proposed scheme is superior in comparison with the conventional NOMA without user grouping and phase rotation‐based user grouping. This improvement is achieved in light of the three positive points of pulse amplitude modulation, the Gray mapping rule, and the joint maximum‐likelihood detector.