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

• Published in: IEEE wireless communications letters Vol. 11; no. 5; pp. 942 - 946
• Main Authors: Huang, Pei-Qiu, Zhou, Yu, Wang, Kezhi, Wang, Bing-Chuan
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.05.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptive algorithms; Algorithms; Array signal processing; Communication systems; differential evolution; Evolutionary algorithms; Evolutionary computation; Intelligent reflecting surface; Mutation; mutation operator; Optimization; Placement; placement optimization; Sociology; Statistics; Time division multiple access; Wireless communication; Wireless communication systems; Wireless communications
• ISSN: 2162-2337; 2162-2345
• DOI: 10.1109/LWC.2022.3151074

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.