Energy-efficient Optimization for IRS-assisted Wireless-powered Communication Networks

Wireless-powered communication is a promising technique to provide convenient and perpetual energy for energy-constrained wireless devices. However, the uplink information transmission of wireless devices in wireless-powered communication networks relies on the harvested energy from the downlink-energy-transfer power station (PS). To tackle this issue, we propose a new intelligent reflecting surface (IRS)-assisted wireless-powered network architecture, where an IRS is deployed between a PS and multiple wireless-powered users to enhance the efficiency of energy harvesting. The total energy efficiency (EE) of all wireless-powered users is maximized by jointly optimizing the energy transfer matrix of the PS, the transmission time and power of users, and the phase shifts of the IRS. The formulated problem is non-convex and challenging to solve. Accordingly, the alternating optimization approach, Dinkelbach’s method, and the variable-substitution approach are used to solve it. Simulation results verify the effectiveness of the proposed algorithm.