Sum throughput optimization of wireless powered IRS-assisted multi-user MISO system

被引:1
|
作者
Xu, Jing [1 ,2 ]
Tang, Jiarun [1 ]
Zou, Yuze [3 ]
Wen, Ruikai [1 ]
Liu, Wei [1 ]
He, Jianhua [4 ]
机构
[1] Huazhong Univ Sci & Technol, Sch Elect Informat & Commun, Wuhan 430074, Peoples R China
[2] Huazhong Univ Sci & Technol, Hubei Key Lab Smart Internet Technol, Wuhan 430074, Peoples R China
[3] Wuhan Maritime Commun Res Inst, Wuhan 430000, Peoples R China
[4] Univ Essex, Sch Comp Sci & Elect Engn, Colchester CO4 3SQ, England
基金
英国工程与自然科学研究理事会;
关键词
Intelligent reflecting surface; Wireless communication; Time switching; Deep reinforcement learning; MU-MISO system; INTELLIGENT; INFORMATION; MODULATION; ENERGY;
D O I
10.1016/j.comnet.2023.109984
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Intelligent reflecting surface (IRS) is a promising technology for beyond-5G wireless communication systems. However, the energy demand of IRS is often overlooked in existing works, leading to performance issues in practical scenarios. To address this issue, this paper proposes an operating model based on time switching (TS) protocol for an IRS-assisted multi-user multiple-input single-output (MISO) system, which can provide energy for IRS through wireless power transfer (WPT) technology. The system throughput maximization problem is addressed to improve performance. Specifically, a two-stage algorithm combined with alternating optimization, denoted as TAO, is proposed. To further improve the optimization process in large-size IRS scenarios, an improved deep deterministic policy gradient (DDPG) method combined with TAO, denoted as TAO-DDPG, is also proposed. Numerical results demonstrate that the proposed TAO-DDPG algorithm achieves similar performance to TAO while greatly reducing the optimization time.
引用
收藏
页数:12
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