Energy-Efficient Intelligent Reflecting Surface Aided Wireless-Powered IIoT Networks

Abstract

This article proposes an energy-efficient intelligent reflecting surface (IRS)-aided wireless-powered industrial Inter-net-of-Things network. The system consists of a multiantenna power station (PS) that transmits wireless radio frequency (RF) power signals, a multiantenna information receiver (IR) that collects RF information signals, and several single-antenna wireless devices (WDs). Harvest-then-transmit protocol is implemented by the WDs. Thus, WDs at first harvest energy from the signals transmitted by PS and then uses the harvested energy to simultaneously transmit information to the IR. We maximize the energy efficiency of the system by jointly optimizing the energy beamformer of the PS, the information receiving beamformer of the IR, IRS phase shift, and the energy/information transfer time. The formulated optimization problem is a nonconvex fractional problem. To tackle the fractional term, the main problem is transformed using the Dinkelbach technique. Then, the transformed problem is decomposed into several subproblems, and a solution is obtained for each subproblem. Following that, a joint solution to the transformed problem is obtained by alternatively optimizing the subproblems. In addition, we obtained computationally low-complex solutions for the proposed system by utilizing fixed beamforming techniques i.e., maximum ratio transmission and zero-forcing-receive beamforming. Numerical results confirm that the proposed system has a better energy efficiency performance compared with the benchmark schemes.