LAUSR

This paper employs game theory to optimize the performance of multiple secondary users (SUs) in a cognitive radio ad hoc network where the primary and SUs have quality of service (QoS) constraints. The proposed algorithm utilizes a distributed noncooperative game theory mechanism among SUs that compete to maximize their individual capacities. We propose two utility functions, UcLog and UcLin, with logarithmic and linear cost functions of the perceived interference in the primary receiver, respectively. The value of the utility function varies according to the transmit power and the relay selection strategy. Simulation results show that both utility functions obtain similar results in most scenarios. However, UcLin causes less interference to the primary receiver and has better convergence than UcLog. The two consecutive games mechanism used in the proposed algorithm allows us to achieve rates above 95% in all simulated scenarios without QoS constraints in secondary links.