Wireless Powered Intelligent Reflecting Surfaces for Enhancing Wireless Communications

Recently, the intelligent reflecting surface (IRS) has become a promising technology for energy-, and spectrum-efficient communications by reconfiguring the radio environment. In this paper, we consider multiple-input single-output (MISO) transmissions from a multi-antenna access point (AP) to a receiver, assisted by a practical IRS with a power budget constraint. The IRS can work in energy harvesting, and signal reflecting phases. It firstly harvests RF energy from the AP's signal beamforming, and then uses it to sustain its operations in the signal reflecting phase. We aim to characterize the maximum capacity by optimizing the AP's transmit beamforming, the IRS's time allocation in two operational phases, and the IRS's passive beamforming to enhance the information rate. To solve the non-convex maximization problem, we exploit its structural properties, and decompose it into two sub-problems in two phases. The IRS's phase shift optimization in the reflecting phase follows a conventional passive beamforming problem to maximize the received signal power. In the energy harvesting phase, the IRS's time allocation, and the AP's transmit beamforming are jointly optimized using monotonic optimization. Simulation results verify the effectiveness of the proposed algorithm.