NOMA Enabled Computation and Communication Resource Trade-off for Mobile Edge Computing

In this paper, we investigate a mobile edge computing (MEC) system in which a set of users with intensive computation tasks, and a set of users with high downlink rate requirement, can cooperate to achieve a mutually-beneficial situation where the task completion time is reduced and the downlink users receive more information from the base station (BS). Specifically, by leveraging uplink and downlink non-orthogonal multiple access (NOMA), the user with an intensive computation task can offload its task bits to the edge cloud and the downlink user. Simultaneously this user relays information to the downlink user from the BS. We consider the joint optimization of computational resource allocation at the edge cloud, communication resource allocation, assignment among the two sets of users, the share of computation, and relay bits to minimize the overall completion time of the tasks while guaranteeing downlink users' incentive requirement. A low complexity iterative algorithm is proposed to find efficient locally optimal solutions by utilizing convex optimization, a graph theory matching algorithm, and block coordinate descent technique. Numerical results show that the proposed technique leads to a significant reduction in users' task completion time and increase in the downlink users rate.