Maximizing the Geometric Mean of User-Rates to Improve Rate-Fairness in Double RIS-Assisted System

被引：2

作者：

Chen, Yufeng ^{[1
]}

Fang, Yong ^{[1
]}

Zhu, Wenbo ^{[2
]}

Tan, Guannan ^{[3
]}

Yu, Hongwen ^{[1
]}

机构：

[1] Shanghai Univ, Sch Commun & Informat Engn, Shanghai 200444, Peoples R China

[2] Univ Technol Sydney, Sch Elect & Data Engn, Broadway, NSW 2007, Australia

[3] Huizhou Speed Wireless Technol Co, Technol Key Project Guangdong Prov, Huizhou 516000, Peoples R China

来源：

2022 11TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND INFORMATION SCIENCES (ICCAIS) | 2022年

关键词：

Reconfigurable intelligent surface (RIS); transmit beamforming; reflection coefficient matrix; geometric mean maximization; COMMUNICATION; DESIGN; PROPER; MIMO;

D O I：

10.1109/ICCAIS56082.2022.9990383

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper proposes a double reconfigurable intelligent surface (RIS)-assisted multi-user downlink communication network with two RISs deployed symmetrically about the base station (BS) for enhancing communication signals. We aim to jointly optimize the beamformers at the BS and the reflection coefficient matrices of the two RISs to maximize the geometric mean (GM) of the users' rates. An efficient alternating descent iteration algorithm based on closed-forms is proposed to address this non-convex problem. Simulation results show that the advantages of the conceived double-RIS system and the viability of the proposed algorithm. Furthermore, our results unveil that the proposed algorithm can significantly improve rate fairness.

引用

页码：203 / 208

页数：6

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