Abstract
In this thesis, we consider two different scenarios of wireless powered communication networks (WPCNs). The first one is a WPCN with two single-antenna access points (APs) and a single-antenna user, where energy and information transfer over multiple time blocks is considered; the other is with two multiple-antenna APs and K single-antenna users, where energy beamforming and receive beamforming designs are considered. For the first scenario, we aim to maximize the system throughput by exploiting time diversity of fading channel. Under an ideal assumption that the channel state information (CSI) are known a priori, the throughput maximization problem can be reformulated as a convex problem, and hence can be optimally solved. Considering the practical causality constraint on CSI, we propose an online algorithm based on reformulating the throughput maximization problem as an energy-efficiency maximization problem. We further present an efficient implementation for the proposed online algorithm to reduce the computational complexity. For the second scenario, to maximize the users’ rate and overcome “doubly-near-far” phenomenon, we maximize the minimum rate among the users by jointly optimizing downlink(DL)-uplink(UL) time allocation, energy beamforming, UL power control and receive beamforming. We propose an efficient successive approximation method for handling this problem and get an approximation solution which has nearly optimal performance compared to the global optimal solution of the state-of-the-art algorithm, which is of high computational complexity.