Energy-Efficient Resource Allocation in TDMS-Based Wireless Powered Communication Networks

This letter considers a wireless powered communication network (WPCN) where users first harvest energy in downlink and then utilize the energy to transmit information signal in uplink simultaneously. Our goal is to maximize the energy efficiency (EE) of the network via joint time allocation and power control. However, directly solving this issue is of significant challenge due to its nonconvex property. By exploiting the nonlinear fractional programming, an iterative resource allocation method based on the Dinkelbach structure is proposed to solve the considered nonconvex optimization problem. In each iteration, we optimize power with fixed time allocation and then optimize time with a given power allocation. Simulation results are presented to show that the system EE is greatly improved by the proposed approach.