Energy-efficient Resource Allocation and Channel Assignment for NOMA-based Mobile Edge Computing

In this paper, we study resource allocation (including power and computation resources) and channel assignment in an uplink Non-orthogonal Multiple Access (NOMA)-based Mobile Edge Computing (MEC) system. Our objective is to minimize the total energy consumption of all users. The problem, however, is a non-convex combinatorial optimization problem. We first investigate the hidden convexity by reformulating the resource allocation problem when the channel assignment is given, and propose an efficient algorithm to allocate the resources by dual decomposition methods. Furthermore, we design a heuristic algorithm to decide the channel assignment leveraging the structural property in the reformulation. Extensive simulations verify that NOMA has great advantages over Orthogonal Multiple Access (OMA) in multi-user latency-intensive MEC systems.