Sum-Rate Maximization for NOMA-Based Networks with D2D Communications using Matching Theory

Non-Orthogonal Multiple Access (NOMA) and (device-to-device) D2D communication is emerging as a prominent technology for the next generation of wireless systems. Based on these, a downlink NOMA-based system with a D2D communication model is proposed. This paper aims to maximize the system sum rate for both cellular users (CUs) and D2D pairs while guaranteeing the minimum (quality of service) QoS requirement of each D2D pair and CU. The original sum-rate maximization problem is non-convex. We decouple the problem into 2 sub-problem, i.e., sub-channel allocation and power allocation, to solve the problem efficiently. Then, a low complexity algorithm based on matching theory is proposed for sub-channel allocation and power allocation is solved by a sequential convex programming method. The Results of the Simulation show efficiency of the proposed algorithms in terms of the system sum-rate.