Joint Trajectory and Resource Allocation Optimization for UAV-Assisted Edge Computing

This paper investigates an unmanned aerial vehicle (UAV) assisted mobile edge computing (MEC) network based on time division multiple access (TDMA) method for ground users. We propose to minimize the total energy consumption through jointly optimizing the 3D UAV trajectory, scheduling design, computation task assignment, transmission power, local and offloading computation resource allocation. To solve the problem with multiple variables, multiple non-convex constraints and non-linear and non-convex objective function, the original problem is decomposed into two subproblems using the alternating optimization, which are scheduling design and joint 3D trajectory and resource allocation optimization. Then an optimization algorithm is proposed based on successive convex approximation (SCA) method. The simulation results show that our joint scheme performances better compared with the benchmark scheme, which also confirms the effectiveness of our method.