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

Author:

Liu Yongfei1,Si Lu12,Wang Yuhuan12,Zhang Bo3,Xu Weizhang12

Affiliation:

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

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

3. Datang Mobile Communications Equipment Co., Ltd., Beijing 100083, China

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.

Funder

Fundamental Research Funds for the Central Universities

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

Reference27 articles.

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4. On the Max-Min Fairness of Beamspace MIMO-NOMA;Jiao;IEEE Trans. Signal Process.,2020

5. Lee, J., and So, J. (2020). Reinforcement Learning-Based Joint User Pairing and Power Allocation in MIMO-NOMA Systems. Sensors, 20.

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