Optimality of Myopic Sensing in Multi-Channel Opportunistic Access

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dc.creatorAhmad, Sahand H. A.
dc.creatorLiu, Mingyan
dc.creatorJavidi, Tara
dc.creatorZhao, Qing
dc.creatorKrishnamachari, Bhaskar
dc.date2008-11-05
dc.date2009-03-10
dc.date.accessioned2026-07-07T12:50:10Z
dc.date.available2026-07-07T12:50:10Z
dc.descriptionWe consider opportunistic communications over multiple channels where the state ("good" or "bad") of each channel evolves as independent and identically distributed Markov processes. A user, with limited sensing and access capability, chooses one channel to sense and subsequently access (based on the sensed channel state) in each time slot. A reward is obtained when the user senses and accesses a "good" channel. The objective is to design the optimal channel selection policy that maximizes the expected reward accrued over time. This problem can be generally cast as a Partially Observable Markov Decision Process (POMDP) or a restless multi-armed bandit process, to which optimal solutions are often intractable. We show in this paper that the myopic policy, with a simple and robust structure, achieves optimality under certain conditions. This result finds applications in opportunistic communications in fading environment, cognitive radio networks for spectrum overlay, and resource-constrained jamming and anti-jamming.
dc.descriptionRevised version
dc.identifierhttps://arxiv.org/abs/0811.0637
dc.identifierhttp://arxiv.org/abs/0811.0637
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/222603
dc.subjectNetworking and Internet Architecture
dc.subjectInformation Theory
dc.titleOptimality of Myopic Sensing in Multi-Channel Opportunistic Access
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