User-IRS Association for Sum-Rate Maximization in Multi-IRS Aided Wireless Communication Networks

被引：1

作者：

Suhail Khan, Zarghuna ^{[1
]}

Mirza, Jawad ^{[1
]}

Obidallah, Waeal J. ^{[2
]}

Alkhathami, Mohammed ^{[2
]}

Alsadie, Deafallah ^{[3
]}

Alsuwailem, Rawan ^{[2
]}

机构：

[1] COMSATS Univ Islamabad, Dept Elect & Comp Engn, Islamabad 45550, Pakistan

[2] Imam Mohammad Ibn Saud Islamic Univ IMSIU, Coll Comp & Informat Sci, Informat Syst Dept, Riyadh 11673, Saudi Arabia

[3] Umm Al Qura Univ, Dept Comp Sci & Artificial Intelligence, Mecca 21961, Saudi Arabia

来源：

IEEE ACCESS | 2024年 / 12卷

关键词：

Array signal processing; Wireless communication; 6G mobile communication; Optimization; MISO communication; Approximation algorithms; Signal to noise ratio; Relays; Phased arrays; Millimeter wave communication; Intelligent reflecting surface; Hungarian algorithm; sum-rate; user association; PERFORMANCE ANALYSIS; INTELLIGENT; 5G;

D O I：

10.1109/ACCESS.2024.3495777

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, we investigate the assignment of intelligent reflecting surfaces (IRSs) to user-base station (BS) pairs in a multi-IRS-assisted wireless communication network. Our objective is to optimize the allocation of one or more IRSs to each user-BS pair to maximize the overall sum-rate of the network. Using passive beamforming, the transmitted signal is directed towards each user through single or multiple IRSs. To achieve optimal user-IRS allocation, we employ the modified Hungarian algorithm. Additionally, we propose a greedy algorithm for user-IRS association, which offers lower complexity than the modified Hungarian algorithm while still aiming to maximize the sum-rate of the network. Simulation results demonstrate the superiority of modified Hungarian algorithm over other techniques. It has been observed that assigning two IRSs per user-BS pair significantly improves the sum-rate compared to assigning a single IRS per user-BS pair. In particular, with the transmission power of 10 dB and 128 reflection coefficients, the modified Hungarian algorithm achieves a sum-rate improvement of approximately 11.6% compared to the greedy algorithm and 20.6% compared to the random IRS assignment.

引用

页码：167224 / 167235

页数：12

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