UAV-Enabled Wireless Power Transfer: Trajectory Design and Energy Optimization

This paper studies a new unmanned aerial vehicle (UAV)-enabled wireless power transfer (WPT) system, where a UAV-mounted mobile energy transmitter (ET) is dispatched to deliver wireless energy to a set of energy receivers (ERs) at known locations on the ground. We investigate how the UAV should optimally exploit its mobility via trajectory design to maximize the amount of energy transferred to all ERs during a finite charging period. First, we consider the maximization of the sum energy received by all ERs by optimizing the UAV’s trajectory subject to its maximum speed constraint. Although this problem is non-convex, we obtain its optimal solution, which shows that the UAV should hover at one single fixed location during the whole charging period. However, the sum-energy maximization incurs a “near-far” fairness issue, where the received energy by the ERs varies significantly with their distances to the UAV’s optimal hovering location. To overcome this issue, we consider a different problem to maximize the minimum received energy among all ERs, which, however, is more challenging to solve than the sum-energy maximization. To tackle this problem, we first consider an ideal case by ignoring the UAV’s maximum speed constraint, and show that the relaxed problem can be optimally solved via the Lagrange dual method. The obtained trajectory solution implies that the UAV should hover over a set of fixed locations with optimal hovering time allocations among them. Then, for the general case with the UAV’s maximum speed constraint considered, we propose a new successive hover-and-fly trajectory motivated by the optimal trajectory in the ideal case, and obtain efficient trajectory designs by applying the successive convex programing (SCP) optimization technique. Finally, numerical results are provided to evaluate the performance of the proposed designs under different setups, as compared to other benchmark schemes. Part of this paper will be presented in the IEEE Global Communications Conference (Globecom) Workshop, Singapore, December 4-8, 2017 [1], and the Asia-Pacific Conference on Communications (APCC) Workshop, Perth, Australia, December 11-13, 2017 [2]. J. Xu is with the School of Information Engineering, Guangdong University of Technology (e-mail: [email protected]). Y. Zeng and R. Zhang are with the Department of Electrical and Computer Engineering, National University of Singapore (e-mail: {elezeng, elezhang}@nus.edu.sg).