Computation Efficiency Maximization and QoE-Provisioning in UAV-Enabled MEC Communication Systems

Since the traditional mobile edge computing (MEC) server is fixed at the edge of the network, it is likely to cause severe propagation loss between the edge server and users. However, ground users can be served when the MEC server is integrated into the unmanned aerial vehicle (UAV) base station (BS). Nevertheless, there are three main factors, including the limited system radio resources, the finite UAV energy and severe interference between the uplink and downlink, that make it challenging for the system to guarantee quality-of-experience of users in the downlink while ensuring the minimum amount of offloading data for users in the uplink. Therefore, this paper investigates computation-efficiency maximization. We jointly optimize computing scheduling, UAV 3D trajectory, bandwidth allocation and transmission power control to maximize the amount of offloaded data, minimize UAV energy consumption, and simultaneously guarantee the QoE of users in the downlink. Due to the nonconvex and nonconcave objective function and the coupling between variables, a multi-stage alternative optimization algorithm is proposed to solve the problem. The simulation results have demonstrated that the computation-efficiency obtained by the proposed scheme is higher than that of other benchmark schemes and meets the QoE demands of users under insufficient resources.