Throughput Maximization Oriented Joint Resource Allocation for Multi-RIS-Assisted MmWave-NOMA Systems

• Published in: IEEE transactions on communications p. 1
• Main Authors: Tang, Kun, Cai, Qihong, Zheng, Beixiong, Xiu, Xin, Feng, Wenjie, Che, Wenquan, Xue, Quan
• Format: Journal Article
• Language: English
• Published: IEEE 2025
• Subjects: alternating optimization (AO); Interference cancellation; joint resource allocation; Millimeter wave communication; Millimeter-wave (MmWave); multiple reconfigurable intelligent surface (RIS); NOMA; non-orthogonal multiple access (NOMA); Optimization; Programming; Reconfigurable intelligent surfaces; Resource management; Simulation; Throughput; Transmission line matrix methods
• ISSN: 0090-6778; 1558-0857
• DOI: 10.1109/TCOMM.2025.3562519

While single reconfigurable intelligent surface (RIS)- aided systems have demonstrated potential in improving transmission performance, their ability to serve multi-user scenarios is inherently limited. In this paper, we investigate the deployment of multiple RISs to assist downlink (DL) millimeter-wave (mmWave) non-orthogonal multiple access (NOMA) communications between a base station (BS) and multiple users. For maximizing the system achievable throughput, we propose a two-stage resource allocation scheme. In the first stage, a two-step RIS-user pairing scheme is proposed by combining the Gale-Shapley (GS) algorithm and the worst connection swapping (WCS) algorithm. In the second stage, based on the pairing results from the first stage, an alternating optimization (AO) algorithm is utilized to iteratively optimize RIS phase shifts, digital precoder, and power allocation. During each iteration, with fixed digital precoder and arbitrary feasible power allocation, the optimal RIS phase shifts can be obtained by the difference of convex (D. C.) programming and semidefinite relaxation (SDR) techniques. Then, the minimum mean-squared error (MMSE)-based digital precoder is adopted. Based on the derived RIS phase shifts and digital precoder, the optimized power allocation can be derived by reusing the D. C. programming subject to the constraint of decoding rate for successive interference cancellation (SIC). Simulation results show that the proposed pairing scheme can achieve near-optimal system achievable throughput, while significantly reducing the computational complexity. In addition, the proposed two-stage resource allocation scheme also demonstrates advantages in improving the overall achievable throughput of the system.