A Novel Nash Bargaining Based Power Allocation Algorithm for MIMO Cognitive Radio Networks

In this study, the power control problem in cognitive radio networks with the spectrum underlay model is considered. The secondary users (SUs) can access the spectrum belonging to primary users (PUs) only if the interference imposed on the PUs is below a certain threshold. All network nodes are assumed to be equipped with multiple antennas. Using game theory approach and the primal decomposition method, a low complexity distributed algorithm based on Nash bargaining solution (NBS) is proposed for spectrum sharing and power allocation for multiple-input multiple output cognitive radio networks. The proposed algorithm is configured in two iterative algorithms, Jacobi and Gauss-Seidel algorithms, and their performance is investigated through simulations. The convergence of the proposed algorithm is further proved analytically. Simulation results show that proposed algorithm achieves an effective tradeoff between fairness and efficiency.