Interference-Aware Resource Allocation Algorithm for D2D-Enabled Cellular Networks Using Matching Theory.

To enhance spectral efficiency and network throughput in Device-to-Device (D2D)-enabled cellular networks, various resource sharing methods can be utilized. However, when users in such dense and complicated networks share the same resources, co-channel interference arises. Therefore, more efficient and comprehensive frameworks should be used to accurately model the network and then decrease co-channel interference and increase resource efficiency. This work proposes a novel and practical resource allocation framework that considers more realistic assumptions based on matching theory with externalities. The goal of the proposed framework is to maximize network throughput by minimizing the interference between co-channel cellular and D2D communications. Moreover, the effect of the interference between various types of communications on the network’s quality of service is studied. The spatial positions of the users’ equipments are modeled by using the Poisson Point Process. It is shown that the proposed method results in a stable resource allocation matching after a finite number of iterations. Based on the analytical and simulation results, the proposed algorithm achieves near-optimal network performance with a low computational cost.