Resource Allocation Strategy in UAV-D2D-Aided Multi-Relay MEC System with Energy Harvesting

In the mobile edge computing (MEC) scenarios, users outside the coverage area of the base station are unable to offload tasks during the offloading process. In this paper, a resource allocation strategy in unmanned aerial vehicle (UAV)-assisted device-to-device (D2D) multi-relay MEC system with energy harvesting is proposed. Multiple UAVs are deployed around the edge of the base station (BS) coverage area. D2D link between users outside the BS coverage area and edge users of BS is controlled by the UAV. Edge users of BS can harvest energy from the UAV. Computing tasks of users outside the BS coverage area can be sent to edge users of BS by different D2D links. Then, edge users of BS can forward computing tasks to the MEC server of BS. Transmitting power, energy harvesting time, computing resources, and channel bandwidth are jointly optimized to minimize the total task completion time. The formulated problem is a non-convex optimization problem. By introducing a series of auxiliary variables, a perspective function is used to convert some non-convex constraints into convex constraints. An alternate iterative optimization algorithm is adopted to obtain the optimal solution to the original problem. Simulation results show that compared with other baseline schemes, the proposed strategy can reduce the total task completion time more effectively.