Let Cognitive Radios Imitate: Imitation-based Spectrum Access for Cognitive Radio Networks

In this paper, we tackle the problem of opportunistic spectrum access in large-scale cognitive radio networks,where the unlicensed Secondary Users (SU) access the frequency channels partially occupied by the licensedPrimary Users (PU). Each channel is characterized by an availability probability unknown to the SUs. We applyevolutionary game theory to model the spectrum access problem and develop distributed spectrum access policiesbased on imitation, a behavior rule widely applied in human societies consisting of imitating successful behavior.We first develop two imitation-based spectrum access policies based on the basic Proportional Imitation (PI) ruleand the more advanced Double Imitation (DI) rule given that a SU can imitate any other SUs. We then adapt theproposed policies to a more practical scenario where a SU can only imitate the other SUs operating on the samechannel. A systematic theoretical analysis is presented for both scenarios on the induced imitation dynamics and theconvergence properties of the proposed policies to an imitation-stable equilibrium, which is also the ǫ-optimum ofthe system. Simple, natural and incentive-compatible, the proposed imitation-based spectrum access policies can beimplemented distributedly based on solely local interactions and thus is especially suited in decentralized adaptivelearning environments as cognitive radio networks.