An Offloading Optimization Scheme for Multi-UAV Aided Network in Mobile Computing

Multiple unmanned aerial vehicles (UAVs) can act as intermediate relay for their flexible mobility. In mobile cloud computing (MCC) and mobile edge computing (MEC), UAVs assist ground user equipments (UEs) to offload traffic to cloudlet or cloud. In this scenario, different UEs may have different quality of experience (QoE) requirement. Moreover, the endurance flying as well as battery limitation of UAVs and UEs make this offloading architecture power sensitive. Thus, UEs' QoE, as well as overall system power consumption should be well-balanced by the MIMO channel assignment and UAVs' trajectory plan. This paper formulates such issue as a non-convex and mixed-integer optimization problem, and further proposes a heuristic joint power and QoE (HJPQ) algorithm to solve it. The numeral simulations reveal the algorithm has great QoE performance with high energy efficiency in different conditions.