Resource Allocation for IRS-Assisted Wireless Powered Communication Networks
Huanqing Cao, Zhendong Li, Wen Chen
Abstract
This letter studies a multi-user intelligent reflecting surface (IRS)-assisted wireless powered communication networks (WPCN) system. Specifically, a multi-antenna energy station (ES) transmits energy signal to multiple single-antenna users assisted by an IRS. Then users use the harvested energy to transmit respective data to a single-antenna information station (IS) assisted by another IRS. Under this setup, we jointly optimize the energy beamforming, IRS phase shift and time slot allocation to maximize the system throughput by applying the alternating optimization (AO) technique, difference-of-convex (DC) programming, penalty-based method and successive convex approximation (SCA). Simulation results verify that the proposed algorithm can improve the system throughput.