Joint Active and Passive Beamforming Optimization for Multi-IRS-Assisted Wireless Communication Systems: A Covariance Matrix Adaptation Evolution Strategy
Tong Yin, Lixin Li, Wensheng Lin, Haixin Hu, Donghui Ma, Junli Liang, Tong Bai, Cunhua Pan, Zhu Han
Abstract
Intelligent reflecting surface (IRS) is applied in 5G and 6G to improve communication performance by reconfiguring signal propagation environments while maintaining low computational complexity and high energy efficiency. This paper proposes a novel methodology of joint active and passive beamforming optimization for wireless communications with the aid of multiple IRSs. In the considered system, the IRSs are deployed to assist the communication link from a multi-antenna access point (AP) to single-antenna users. We maximize the received signal to noise ratio (SNR) and sum rate of the multi-IRS-assisted communication system for single user and multiple users respectively, by solving a joint optimization problem of the active beamforming at the AP and the reflection beamforming at the IRSs. Specifically, we develop a mechanism of joint beamforming optimization for multi-IRS-assisted communications based on covariance matrix adaptation evolution strategy (CMA-ES), namely the BO-CMA algorithm, to jointly consider both the AP active beamforming and IRS reflection beamforming in the dynamic signal propagation environment. Furthermore, simulation results are provided to show that the BO-CMA algorithm is capable of significantly outperforming the benchmark schemes. Consequently, the solution based on the BO-CMA algorithm can dynamically rebuild the signal propagation environment, and improve the received SNR and the sum rate respectively for multi-IRS-assisted one user and multiple users communications.