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Blind cognitive-MAC: A Bayesian game theoretic perspective

The proposed blind cognitive-MAC (BC-MAC) protocol highlights a practical approach for the cognitive system designer. Using the Bayesian game theoretic approach coupled with the proposed Bayesian learing/ reasoning (BLA) for the self-awareness of the secondary users (SUs), the cognitive radios can always learn the actually changing curve of the cognitive environment. This will help the SUs to make the right selection of the transmission strategy. We conclude that the Bayesian equilibrium solutions for the BC-MAC protocol exist under some minor conditions, and the presented BLA can rationally learn the context after a few conflicts and collisions. Numerical results verify these consecutions and show that the performance can be improved a lot measured by signal-to-interference.