In this paper, first we briefly describe the differences in the workingprinciples of uplink and downlink NOMA transmissions. Then, for both uplink anddownlink NOMA, we formulate a sum-throughput maximization problem in a cellsuch that the user clustering (i.e., grouping users into a single cluster ormultiple clusters) and power allocations in NOMA cluster(s) can be optimizedunder transmission power constraints, minimum rate requirements of the users,and SIC constraints. Due to the combinatorial nature of the formulated mixedinteger non-linear programming (MINLP) problem, we solve the problem in twosteps, i.e., by first grouping users into clusters and then optimizing theirrespective power allocations. In particular, we propose a low-complexitysub-optimal user grouping scheme. The proposed scheme exploits the channel gaindifferences among users in a NOMA cluster and group them into a single clusteror multiple clusters in order to enhance the sum-throughput of the system. Fora given set of NOMA clusters, we then derive the optimal power allocationpolicy that maximizes the sum throughput per NOMA cluster and in turn maximizesthe overall system throughput. Using KKT optimality conditions, closed-formsolutions for optimal power allocations are derived for any cluster size,considering both uplink and downlink NOMA systems. Numerical results comparethe performance of NOMA over orthogonal multiple access (OMA) and illustratethe significance of NOMA in various network scenarios.
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