Abstract
This paper introduces a tractable priority-index multichannel sensing policy in a discrete-time model of opportunistic spectrum access for cognitive radio networks, which aims to be close to optimal under a discounted or average throughput minus sensing cost performance objective. The policy dynamically allocates transmission opportunities arising in a collection of asymmetric channels licensed to primary users to a set of secondary unlicensed users. Channel availabilities follow independent binary-state Markov dynamics, and are partially observed via error-prone spectrum sensors. The paper formulates the model as a multiarmed restless bandit problem with real-state projects, and then deploys Whittle’s (1988) marginal productivity (MP) index policy. The challenging issues of indexability (existence of the index) and efficient index evaluation are resolved by deploying recent results of the author for real-state restless bandit indexation. Preliminary computational results are reported showing that the MP policy can achieve substantial gains over the myopic and random policies.
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Niño-Mora, J. (2009). A Restless Bandit Marginal Productivity Index for Opportunistic Spectrum Access with Sensing Errors. In: Núñez-Queija, R., Resing, J. (eds) Network Control and Optimization. NET-COOP 2009. Lecture Notes in Computer Science, vol 5894. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10406-0_5
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DOI: https://doi.org/10.1007/978-3-642-10406-0_5
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