Joint Optimization of Resource Allocation and UAVs’ Trajectories in Multi-UAV-Aided MEC Systems

Abstract

The combination of unmanned aerial vehicles (UAVs) and mobile edge computing (MEC) has become an up-and-coming technique to provide additional computing support for smart mobile devices with limited battery capacity in the wireless communication network systems. In this paper, a multi-UAV-aided MEC system is modelled where UAVs are equipped with MEC servers and users can execute local computing and computation offloading to UAVs simultaneously. The total amount of processing bits of all users is maximized by the joint optimization of the user-UAV association, local processing frequency, transmit power, bandwidth allocation and UAVs’ trajectories, meanwhile, the energy consumption constraint and the UAVs’ speed constraint are satisfied. Because the formulated problem is not convex, it is challenging to get the global optimal solution directly. To iron out the non-convex problem, it is divided into three subproblems and solved by an alternating optimization algorithm. Simulations show that the algorithm introduced in our paper performs better than the local computing, full offloading and fixed trajectory patterns.