Interference-aware channel allocation algorithm with game theoretic approach for cognitive radio networks

In cognitive radio networks, the Secondary Users (SUs) are allowed to utilize unused portions of the licensed spectrum to enhance the performance and efficiency of the channel resource in networks. However, with the increasing number of wireless devices and users competence for the limited channel resource, the channel allocation problem has become an important issue in the cognitive radio networks. Moreover, the interference in communication has become an important factor that affects the efficiency of transmission in cognitive radio networks. In this paper, we proposed an algorithm with game theoretic approach to solve the problem of channel allocations in cognitive radio networks, based on interference aware information between communication pairs. By game theory, the channel allocations of SUs are proposed by their perceived utilities associated with possible actions of neighboring users. The effectiveness of the communication links is determined by the bandwidth of the available channels to the SUs and the heterogeneous interference range between the communication links. Our proposed algorithm can achieve Nash Equilibrium convergence in the game theory.