Imitation-Based Spectrum Access Policy for Cognitive Radio Networks
In this paper, the authors tackle the problem of opportunistic spectrum access in cognitive radio networks. They consider a large number of unlicensed Secondary Users (SU) accessing a number of frequency channels partially occupied by licensed Primary Users (PU). Each channel is characterized by an unknown availability probability. They apply evolutionary game theory to model the spectrum access problem and propose imitation-based spectrum access policies based on the Proportional Imitation Rule (PIR) and Double Imitation (DI) rule. They show that both policies converge exponentially in time to the Nash Equilibrium which is also the system optimum. The proposed spectrum access policies are evaluated by simulations which demonstrate their convergence to a stable equilibrium state which is also the system optimum.