Trajectory Optimization and Resource Allocation for Time Minimization in the UAV-Enabled MEC System

The unmanned aerial vehicles (UAVs) have been widely used in civilian environments, due to its high flexibility, low cost and ease of deployment. In this paper, an UAV-enabled mobile edge computing (MEC) system is studied, in which the UAV serves as an aerial mobile base station to provide services for a group of ground user equipments (UEs) with computation task requests. We jointly optimize the time allocation, resource allocation and the UAV flying trajectory to minimize the time required for the UAV to complete the task, subject to the constraints of different kinds of resources, energy and velocity. Due to the non-convexity of the formulated problem, we first transform it to a feasibility check problem and then divide it onto three convex optimization subproblems. By using the block coordinate descent method and the successive convex approximate (SCA) method, we propose an efficient iterative algorithm to solve the three subproblems alternately with ensured convergence. Extensive simulation results show that the proposed joint optimization algorithm reduces the task completion time compared with other schemes.