Resource Configuration for Throughput Maximization in UAV-WPCN With Intelligent Reflecting Surface

UAV-based wireless powered communication network is a promising method of power supply for battery-free IoT devices, but the limited wireless transmission capability of the UAV constrains the coverage area and transmission throughput. This paper aims to address this issue by exploring intelligent reflecting surfaces with optimized configurations, including the number of reflective elements, transmission power, and the UAV's altitude. The scheme design is challenging because such a throughput maximization problem is essentially a non-convex optimization problem due to the random wireless channel state and the unknown probability distribution of the objective function. By sequentially applying alternating optimization, successive convex approximation, penalty function, and difference-convex optimization, the schemes proposed in this paper can transform the original non-convex optimization problem into a convex one. Extensive evaluation proves the efficacy of the proposed scheme. The paper further compares two settings of the intelligent reflecting surface, namely dynamic phase shift and static phase shift, and provides their performance gap.