Placement Optimization for Multi-IRS-Aided Wireless Communications: An Adaptive Differential Evolution Algorithm
Pei-Qiu Huang, Yu Zhou, Kezhi Wang, Bing-Chuan Wang
Abstract
Using intelligent reflecting surfaces (IRSs) is a promising approach to enhance the performance of wireless communication systems. In this letter, 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.