Energy Efficiency Maximization for mmWave WPCN With Dynamic Multi-Steerable Energy Beamforming

This paper proposes a dynamic multi-steerable energy beam scheme for millimeter-wave (mmWave) wireless-powered communication network (WPCN) and studies its resource allocation. In the considered system, a hybrid access point (HAP) transmits radio frequency (RF) energy beams to multiple sensors for their wireless energy harvesting (WEH) in downlink (DL) and then receives signals from the sensors in uplink (UL). During the DL phase, a beam splitting technique is adopted to opportunistically generate multiple analog sub-beams for serving multiple sensors with arbitrary angle-of-departure (AoD) distribution, which can provide more flexibility and improve usability for the mmWave-based WPCNs. Then, we design a two-stage resource allocation method for improving the WEH efficiency of all sensors during the DL and maximizing the energy efficiency (EE) of the system during the UL. In the first stage, by utilizing the coalition formation game theory and linear optimization method, a joint sensor grouping, antenna allocation, and power allocation algorithm is proposed to maximize the conditional harvested RF power of all sensors by fixing transmission timeslot allocation of the DL and UL. In the second stage, by utilizing the obtained optimal information in the first stage, a solution based on Dinkelbach algorithm and Lagrange dual method is devised to solve the optimization problem of transmission timeslot allocation for maximizing of the system's EE. The numerical results demonstrate that the designed resource allocation method for WEH in the DL can achieve an approximately optimal performance, while the whole two-stage resource allocation method offers an obvious EE improvement compared to that of the proposed multi-beam scheme without optimal resource allocation and conventional single-beam scheme.