α-Fairness-based joint power allocation and power splitting for massive MIMO systems with SWIPT

被引:6
|
作者
Li, Hao [1 ,2 ,3 ]
Yang, Shuo [3 ]
Wen, Zhicheng [3 ]
Cao, Jiawei [3 ]
Luo, Guangkun [3 ]
Wang, Zhigang [3 ]
Wang, Houjun [3 ]
机构
[1] Univ Elect Sci & Technol China, Shenzhen Inst Adv Study, Shenzhen, Peoples R China
[2] ShenZhen Silver Star Intelligent Technol Co Ltd, Shenzhen, Peoples R China
[3] Univ Elect Sci & Technol China, Sch Automat Engn, Chengdu, Peoples R China
关键词
Massive MIMO; Power allocation; Power splitting; SWIPT; RESOURCE-ALLOCATION; WIRELESS; OPTIMIZATION; MAXIMIZATION; INFORMATION; NETWORKS;
D O I
10.1016/j.dsp.2021.103219
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Fairness with a alpha parameter is an important consideration to provide uniform and high quality service for each user when designing a wireless communication system. In general, alpha-fairness problem includes the proportional fairness and the max-min fairness. In this paper, we consider the problem of alpha-fairness-based joint power allocation and power splitting for massive multiple-input and multiple-output (MIMO) systems with simultaneous wireless information and power transfer (SWIPT). Different from the existing works, we utilize a low-complexity parametric optimization method to solve the non-convex proportional fairness problem. Furthermore, we develop a joint iterative algorithm to solve the general alpha-fairness problem and obtain the suboptimal solutions on power allocation and power splitting. Simulation results illustrate the performance of the proposed algorithm. (c) 2021 Published by Elsevier Inc.
引用
收藏
页数:7
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