A game-theoretic approach for dynamic spectrum sharing in cognitive radio networks

In a spectrum sharing system, lower-priority users are allowed to spatially reuse the spectrum allocated to higher-priority users as long as they do not disrupt communications of the latter. Therefore, to improve spectrum utilization, an important requirement for the former users is to manage the interference and ensure that the latter users can maintain reliable communications. This paper presents a game theoretic framework to model the dynamic spectrum sharing in cognitive radio networks. First, a utility function that captures the selfish and cooperative behavior of the lower-priority users to manage the interference by selecting the best channel with minimal intra- and inter-system interference is defined. Next, based on the defined utility function, the proposed framework can be formulated as a potential game; thus, the convergence to a Nash equilibrium point is ensured as long as the best response dynamic is adopted. At the equilibrium point, power allocation algorithm is proposed such that the interference to higher-priority users can be maintained below the maximum allowable level. The simulation results show the convergence of the proposed potential game and the performance improvement of higher-priority users in terms of SINR and outage probability.