Energy-Efficient Optimization Design for UAV-Assisted Wireless Powered MEC Systems

The quality of services requirements of wireless networks are always limited by devices’ on-board computation capabilities and batteries. Considering the advantages of Unmanned aerial vehicles, such as high mobility and probability of line-of-sight links, this paper proposes a UAV-assisted wireless powered mobile edge computing system in 5G networks, where the UAV is dispatched as a cloud-let and a flying energy source to provide the energy transferring and task offloading services to IoTDs. To promote the green communication and prolong the duration of system service, we intend to minimize the weighted system energy consumption by jointly optimizing the working mode decisions, IoTD associations, charging resource allocations, which is a non-convex problem with the mixed integer variables. Therefore, an efficient alternative algorithm is developed to obtain the high-quality sub-optimal solutions based on the block-coordinate descent optimization technique. Additional, the experimental results show that the proposed algorithm is superior to the benchmarks.