Computation Throughput Maximization for UAV-Enabled MEC via Uplink NOMA

Non-Orthogonal Multiple Access (NOMA) allows for the sharing of communication link resources among multiple users, which increases spectrum efficiency. In this paper, we consider the NOMA-based mobile edge computing (MEC) networks with unmanned aerial vehicle (UAV), where convenient computation offloading services for ground devices (GDs) with NOMA is provided. The main focus is to investigate the computation capacity in terms of computation throughput, which is characterized by the total size of completed tasks achieved through air-ground collaboration. To guarantee the fairness of GDs, the minimum computation throughput for all GDs is maximized by jointly designing the UAV trajectory, channel relationship coefficient, and computation resource allocation, where the formulated problem is non-convex with closely coupled mixed-integer design variables. A novel penalty based iterative algorithm is proposed, where penalty term is employed to penalize non-integer solution and an inexact block coordinate decent method is adopted to avoid strong locality of the optimized solution, where the convergence is also proved. We conduct extensive simulations and show that our joint design algorithm outperforms other benchmark schemes.