Upper Confidence Bound Algorithm for Opportunistic Spectrum Access With Sensing Errors

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In this paper, the authors consider the problem of exploiting spectrum resources within the Opportunistic Spectrum Access context. They mainly focus on the case where one Secondary User (SU) probes a pool of possibly available channels dedicated to a primary network. The SU is assumed to have imperfect sensing abilities. They, first, model the problem as a Multi-Armed Bandit problem with sensing errors. Then, they suggest to analyze the performances of the well known Upper Confidence Bound algorithm UCB within this framework, and show that they still can obtain an order optimal channel selection behavior.