Distributed Throughput and Energy Efficient Resource Optimization When D2D and Massive MIMO Coexist

Fifth generation (5G) cellular networks intend to overcome the challenging demands posed by dynamic service quality requirements, which are not achieved by single network technology. The future cellular networks require efficient resource allocation and power control schemes that meet throughput and energy efficiency requirements when multiple technologies coexist and share network resources. In this paper, we optimize the throughput and energy efficiency (EE) performance for the coexistence of two technologies that have been identified for the future cellular networks, namely, massive multiple-input multiple-output (MIMO) and network-assisted device-to-device (D2D) communications. In such a hybrid network, the co/cross-tier interferences between cellular and D2D communications caused by spectrum sharing is a significant challenge. To this end, we formulate the average sum rate and EE optimization problem as mixed-integer non-linear programming (MINLP). We develop distributed resource allocation algorithms based on matching theory to alleviate interferences and optimize network performance. It is shown in this paper that the proposed algorithms converge to a stable matching and terminate after finite iterations. Mat-lab simulation results show that the proposed algorithms achieved more than 88% of the average transmission rate and 86% of the energy efficiency performance of the optimal matching with lower complexity.