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The combination of non-orthogonal multiple access (NOMA) and mobile edgecomputing (MEC) can significantly improve the spectrum efficiency beyond thefifth-generation network. In this paper, we mainly focus on energy-efficientresource allocation for a multi-user, multi-BS NOMA assisted MEC network withimperfect channel state information (CSI), in which each user can upload itstasks to multiple base stations (BSs) for remote executions. To minimize theenergy consumption, we consider jointly optimizing the task assignment, powerallocation and user association. As the main contribution, with imperfect CSI,the optimal closed-form expressions of task assignment and power allocation areanalytically derived for the two-BS case. Specifically, the original formulatedproblem is nonconvex. We first transform the probabilistic problem into anon-probabilistic one. Subsequently, a bilevel programming method is proposedto derive the optimal solution. In addition, by incorporating the matchingalgorithm with the optimal task and power allocation, we propose a lowcomplexity algorithm to efficiently optimize user association for themulti-user and multi-BS case. Simulations demonstrate that the proposedalgorithm can yield much better performance than the conventional OMA schemebut also the identical results with lower complexity from the exhaustive searchwith the small number of BSs.

Energy-Efficient Resource Allocation for NOMA enabled MEC Networks with Imperfect CSI