Placement Optimization for Multi-IRS-Aided Wireless Communications: An Adaptive Differential Evolution Algorithm

Huang, Pei-Qiu, Zhou, Yu, Wang, Kezhi and Wang, Bing-Chuan (2022) Placement Optimization for Multi-IRS-Aided Wireless Communications: An Adaptive Differential Evolution Algorithm. IEEE Wireless Communications Letters. pp. 1-5. ISSN 2162-2337 (In Press)

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Placement_Optimization_for_Multi-IRS-Aided_Wireless_Communications_An_Adaptive_Differential_Evolution_Algorithm.pdf - Accepted Version

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Official URL: https://doi.org/10.1109/LWC.2022.3151074

Abstract

Using intelligent reflecting surfaces (IRSs) is a promising approach to enhance the performance of wireless communication systems. In this paper, the placement optimization of multi-IRSs is investigated in multi-IRS-aided wireless communication systems, with the aim of minimizing the number of IRSs subject to the average achievable data rate. Then, an adaptive differential evolution algorithm is developed to jointly optimize the number, locations, and phase shift coefficients of IRSs, in which a novel strategy is devised to adaptively select the mutation operator for each individual. Compared with other algorithms, the proposed algorithm performs well in reducing the number of IRSs while satisfying the average achievable data rate.

Item Type: Article
Additional Information: Funding information: Research funded by National Natural Science Foundation of China (62106287).
Uncontrolled Keywords: Intelligent reflecting surface, placement optimization, differential evolution, mutation operator
Subjects: G600 Software Engineering
H600 Electronic and Electrical Engineering
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: John Coen
Date Deposited: 21 Mar 2022 10:45
Last Modified: 21 Mar 2022 10:45
URI: http://nrl.northumbria.ac.uk/id/eprint/48703

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