Adaptation in a Channel Access Game with Private Monitoring

Abstract

Under the opportunistic spectrum access paradigm, the shared pool of spectrum bands that the multiple autonomous cognitive radios (CRs) need to compete for is not necessarily homogeneous. The non-homogeneity in channels may lead to payoff distribution conflict among autonomous CRs, as each CR would prefer the outcome in which it selects the more desirable channels. To address this challenge, we have designed an adaptive strategy that (without explicit coordination) enables the CRs to autonomously reach an outcome that maximizes the total CR network throughput and minimizes the payoff distribution conflict among the CRs. We utilize the framework of repeated games with private monitoring to: 1) study the dynamic channel selection problem; 2) analyze the stability of the proposed strategy; and 3) investigate the impact of deviations by a selfish CR on the performance of the proposed strategy. In our model, multiple autonomous CRs are not able to observe the channel selections of other competing CRs. Rather, they get a signal from which the selections must be inferred.