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A restless multi-armed bandit problem that arises in multichannelopportunistic communications is considered, where channels are modeled asindependent and identical Gilbert-Elliot channels and channel stateobservations are subject to errors. A simple structure of the myopic policy isestablished under a certain condition on the false alarm probability of thechannel state detector. It is shown that the myopic policy has a semi-universalstructure that reduces channel selection to a simple round-robin procedure andobviates the need to know the underlying Markov transition probabilities. Theoptimality of the myopic policy is proved for the case of two channels andconjectured for the general case based on numerical examples.

Structure and Optimality of Myopic Policy in Opportunistic Access with Noisy Observations