Resource allocation for sum-rate maximization in NOMA-based generalized spatial modulation

• Published in: Digital communications and networks Vol. 8; no. 6; pp. 1077 - 1084
• Main Authors: Li, Guoquan, Hong, Zijie, Pang, Yu, Xu, Yongjun, Huang, Zhengwen
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.12.2022; School of Communication and Information Engineering,Chongqing University of Posts and Telecommunications,Chongqing,400065,China; Chongqing Key Laboratory of Photoelectronic Information Sensing and Transmitting Technology,Chongqing,400065,China%Chongqing Key Laboratory of Photoelectronic Information Sensing and Transmitting Technology,Chongqing,400065,China%School of Communication and Information Engineering,Chongqing University of Posts and Telecommunications,Chongqing,400065,China%Department of Electronic and Electrical Engineering Brunei University London,London,UB8-3PH,UK; KeAi Communications Co., Ltd
• Subjects: NOMA; Power allocation; Resource allocation; Spatial modulation; User grouping; NOMA; User grouping; Spatial modulation; Power allocation; Resource allocation
• ISSN: 2352-8648; 2468-5925; 2352-8648
• DOI: 10.1016/j.dcan.2022.02.005

The Multiple-Input Multiple-Output (MIMO) Non-Orthogonal Multiple Access (NOMA) based on Spatial Modulation (SM-MIMO-NOMA) system has been proposed to achieve better spectral efficiency with reduced radio frequency chains comparing to the traditional MIMO-NOMA system. To improve the performance of SM-MIMO-NOMA systems, we extend them to generalized spatial modulation scenarios while maintaining moderate complexity and fairness. In this paper, system spectral efficiency and transmission quality improvements are proposed by investigating a sum-rate maximization resource allocation problem that is subject to the total transmitted power, user grouping, and resource block constraints. To solve this non-convex and difficult problem, a graph-based user grouping strategy is proposed initially to maximize the mutual gains of intragroup users. An auxiliary-variable approach is then adopted to transform the power allocation subproblem into a convex one. Simulation results demonstrate that the proposed algorithm has better performance in terms of bit error rate and sum rates.