Optimal Resource Allocation for 6G UAV-enabled Mobile Edge Computing with Mission-Critical Applications

This paper considers unmanned aerial vehicle (UAV)-enabled mobile edge computing (MEC) for the sixth generation (6G) networks with mission-critical applications. In particular, the UAVs serve as mobile edge servers to execute offloaded tasks from constrained Internet of things (IoT) devices. A low complexity optimisation algorithm is proposed to deal with the latency minimisation problem of task execution. More specifically, the solution jointly optimises bandwidth allocation and task offloading probability subject to quality-of-service constraints and energy budget of devices. Numerical results validate the effectiveness of the proposed algorithm in terms of convergence behaviour and impacts of various system parameters.