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

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

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...

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Bibliographic Details
Published in:IEEE access Vol. 12; p. 1
Main Authors: Khan, Zarghuna Suhail, Mirza, Jawad, Obidallah, Waeal J., Alkhathami, Mohammed, Alsadie, Deafallah, Alsuwailem, Rawan
Format: Journal Article
Language:English
Published: Piscataway IEEE 01-01-2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
6G mobile communication
Algorithms
Approximation algorithms
Array signal processing
Beamforming
Communication networks
Greedy algorithms
Hungarian algorithm
Intelligent reflecting surface
Millimeter wave communication
MISO communication
Optimization
Phased arrays
Reconfigurable intelligent surfaces
Relays
Signal to noise ratio
Sum-rate
User association
Wireless communication
Wireless communications
Wireless networks
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Summary: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.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2024.3495777