LAUSR

Internet of Things (IoT) devices usually lack perpetual power supply since they are generally deployed at remote areas with limited battery capacities. Moreover, the computing power of the IoT devices is usually limited and the generated data need to be offloaded to a more powerful computing server for further processing. In this article, we study a novel unmanned aerial vehicle (UAV)-enabled IoT network, where the UAV delivers energy to the ground IoT devices by employing wireless power transfer (WPT) in the downlink and collects data in the uplink. In our work, we try to minimize the total energy consumption of the UAV by determining the trajectory and charging power of the UAV, the resource allocation, and the transmission scheme subject to task collection and resource budget requirements. To make the formulated problem more tractable, we decompose the primal problem into three subproblems (i.e., the transmission association problem, the trajectory design problem, and the resource allocation problem) and utilize the block coordinate descent (BCD) method to solve them alternately. Since the trajectory design problem is still highly nonconvex, we further transform it into a convex one by leveraging the successive convex approximation (SCA) technique. In the simulation, we provide extensive numerical results to corroborate the effectiveness of our proposed algorithm.