Game Theoretic Resource Allocation for D2D MIMO Heterogenous Networks

In this paper, we formulate a sum-rate maximization problem for device-to-device (D2D) communications underlaying downlink multiple-input multiple-output heterogenous cellular networks subject to the quality of service constraints and the interference temperature constraint. Since it is difficult to obtain the optimal solution due to the high complexity, game theory is used to study the resource allocation in such networks. The proposed game is a potential game where the existence of Nash equilibrium (NE) is guaranteed. A practical resource allocation algorithm based on better response dynamic is proposed. We prove that the proposed algorithm can converge to a feasible NE. Numerical results show that the proposed algorithm can achieve near optimal sum rate performance with low complexity.