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用于最大化波束空间MIMO-NOMA系统频谱效率的高效预编码和功率分配技术

Efficient Precoding and Power Allocation Techniques for Maximizing Spectral Efficiency in Beamspace MIMO-NOMA Systems.

作者信息

Liu Yongfei, Si Lu, Wang Yuhuan, Zhang Bo, Xu Weizhang

机构信息

Engineering Research Center of Digital Audio & Video Ministry of Education, Communication University of China, Beijing 100024, China.

State Key Laboratory of Media Convergence & Communication, Communication University of China, Beijing 100024, China.

出版信息

Sensors (Basel). 2023 Sep 20;23(18):7996. doi: 10.3390/s23187996.

Abstract

Beamspace MIMO-NOMA is an effective way to improve spectral efficiency. This paper focuses on a downlink non-orthogonal multiple access (NOMA) transmission scheme for a beamspace multiple-input multiple-output (MIMO) system. To increase the sum rate, we jointly optimize precoding and power allocation, which presents a non-convex problem. To solve this difficulty, we employ an alternating algorithm to optimize the precoding and power allocation. Regarding the precoding subproblem, we demonstrate that the original optimization problem can be transformed into an unconstrained optimization problem. Drawing inspiration from fraction programming (FP), we reconstruct the problem and derive a closed-form expression of the optimization variable. In addition, we effectively reduce the complexity of precoding by utilizing Neumann series expansion (NSE). For the power allocation subproblem, we adopt a dynamic power allocation scheme that considers both the intra-beam power optimization and the inter-beam power optimization. Simulation results show that the energy efficiency of the proposed beamspace MIMO-NOMA is significantly better than other conventional schemes.

摘要

波束空间MIMO-NOMA是提高频谱效率的有效方法。本文重点研究波束空间多输入多输出(MIMO)系统的下行非正交多址(NOMA)传输方案。为了提高和速率,我们联合优化预编码和功率分配,这是一个非凸问题。为了解决这一难题,我们采用交替算法来优化预编码和功率分配。对于预编码子问题,我们证明了原优化问题可以转化为无约束优化问题。借鉴分式规划(FP),我们重构问题并推导优化变量的闭式表达式。此外,我们利用诺伊曼级数展开(NSE)有效降低了预编码的复杂度。对于功率分配子问题,我们采用一种动态功率分配方案,该方案同时考虑了波束内功率优化和波束间功率优化。仿真结果表明,所提出的波束空间MIMO-NOMA的能量效率明显优于其他传统方案。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3cfe/10534327/5ca2874e2253/sensors-23-07996-g001.jpg

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