UAV-Aided Low Latency Mobile Edge Computing with mmWave Backhaul

Recently, unmanned aerial vehicle (UAV) has been considered as a promising technique in mobile edge computing networks, and enhances the performances of ultra-reliable and low-latency services. In this paper, we propose a UAV-aided low latency mobile edge computing network with millimeter wave (mmWave) backhaul. There are two types of communication links in our network, the UAV link and the ad hoc link. We jointly consider the network resource allocation and the UAV trajectory design in our proposed problem, which is a non-convex mixed integer nonlinear programming (MINLP). For solving the proposed problem, we give a novel algorithm framework. We adopt generalized Benders decomposition (GAD) as the outer loop algorithm to separate the integer variables and continuous variables. In the inner loop, the continuous primal problem is solved by the joint alternating direction method of multipliers (ADMM), Dinkelbach algorithm and successive convex approximation (SCA) algorithm. The simulation results show that our proposed system architecture and algorithm framework can achieve low latency for the time-sensitive task in mobile edge computing.