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In mobile communication systems, device-to-device (D2D) communication and nonorthogonal multiple access (NOMA) are effective ways to improve spectrum efficiency and system throughput. In the NOMA-based D2D system, social relationship among D2D users is introduced to form D2D clusters, and NOMA is used for many-to-one communication in each D2D cluster. This paper proposes a joint channel allocation and power control algorithm which decomposes the resource allocation problem into two subproblems: channel allocation and power control. Matching theory is utilized to allocate channels for D2D clusters and sequential convex programming is applied to transform the optimization target to a convex problem before solving it via genetic algorithm. Simulation results indicate the superiority of our algorithm in improving the system throughput on the basis of meeting users’ needs for files.

Social-Aware-Based Resource Allocation for NOMA-Enhanced D2D Communications