Hybrid model of inter-stage spectrum trading in multistage game-theoretic framework

Dynamic spectrum access (DSA), consisting of spectrum sharing and spectrum trading stage, becomes a promising approach to increase the efficiency of spectrum usage and system performance. In this paper, from the perspective of individual interest optimization, we focus on strategy adaptation of network users and their interaction in spectrum trading process. Considering adverse effects on decision-making accuracy and the fairness among network users via local information acquirement, a hybrid game model based on global information of relevant spectrum is proposed to formulate intelligent behaviors of both primary and secondary users. Specifically, by using the evolutionary game theory, a spectrum-selection approach for the evolution process of secondary users is designed to converge to the evolutionary equilibrium gradually. Moreover, competition among primary users is modeled as a non-cooperative game and an iterative algorithm is employed to achieve the Nash equilibrium. The simulation results show that the proposed hybrid game model investigates network dynamics under different network parameter settings.