Full-Duplex-Enhanced Wireless-Powered Backscatter Communication Networks: Radio Resource Allocation and Beamforming Joint Optimization

Abstract

Backscatter communication, as an important technique in green Internet of Things, has been concerned by academic and industry to improve system capacity and simultaneously reduce network cost in a low-power-consumption way. In this paper, a sum-throughput maximization resource allocation (RA) problem is studied for a full-duplex-enhanced wireless-powered backscatter communication network, where one hybrid access point (HAP) with constant power supply can coordinate wireless energy and information transmission for multiple backscatter users without other energy sources. All users first harvest the wireless energy from the HAP during the downlink transmission and simultaneously backscatter their information to the HAP, and then send their information to the HAP during uplink transmission. Then, a sum-throughput maximization RA problem is formulated by jointly optimizing the beamforming vector of the HAP, energy-harvesting (EH) time, reflection coefficients, and the transmit power of users, where the constraints of the maximum transmit power imposed by the HAP, the minimum throughput and the EH requirement of each user are considered simultaneously. Finally, the non-convex problem is converted into a convex one by applying a series of convex optimization methods, then an iterative-based RA algorithm is proposed to solve it. Simulation results verify the effectiveness of the proposed algorithm.