Abstract : In this paper, we tackle the problem of opportunistic spectrum access in large- scale cognitive radio networks, where the unlicensed Secondary Users (SU) ac- cess the frequency channels partially occupied by the licensed Primary Users (PU). Each channel is characterized by an availability probability unknown to the SUs. We apply population game theory to model the spectrum access prob- lem and develop distributed spectrum access policies based on imitation, a be- havior rule widely applied in human societies consisting of imitating successful behaviors. We develop two imitation-based spectrum access policies based on the basic Proportional Imitation (PI) rule and the more advanced Double Imi- tation (DI) rule given that a SU can only imitate the other SUs operating on the same channel. A systematic theoretical analysis is presented for both policies on the induced imitation dynamics and the convergence properties of the proposed policies to the Nash Equilibrium. Simple and natural, the proposed imitation- based spectrum access policies can be implemented distributedly based on solely local interactions and thus is especially suited in decentralized adaptive learning environments as cognitive radio networks.
