Radio-Map-Based Robust Positioning Optimization for UAV-Enabled Wireless Power Transfer

This letter studies an unmanned aerial vehicle (UAV)-enabled wireless power transfer (WPT) system, in which a UAV-mounted energy transmitter (ET) optimizes its positioning locations over time to efficiently charge a set of energy receivers (ERs) distributed on the ground. Different from conventional designs based on deterministic (e.g., line-of-sight (LoS)) or stochastic (e.g., probabilistic LoS) channel models, we consider a new radio-map-based design approach, in which the UAV exploits the information of channel propagation environments for efficient positioning optimization. By practically assuming that the UAV only partially knows the ERs' locations, our objective is to maximize the minimum energy transferred to all ERs over a particular charging duration that is sufficiently long. By applying the robust optimization and Lagrange duality method, we obtain an efficient solution to the minimum energy maximization problem, which has an interesting multi-location-positioning structure. Numerical results show that our proposed radio-map-based robust design significantly improves the WPT performance, as compared to conventional designs based on LoS and probabilistic LoS channel models.