A maximum entropy approach to OFDM channel estimation

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dc.creatorCouillet, Romain
dc.creatorDebbah, Merouane
dc.date2008-11-05
dc.date.accessioned2026-07-07T10:15:44Z
dc.date.available2026-07-07T10:15:44Z
dc.descriptionIn this work, a new Bayesian framework for OFDM channel estimation is proposed. Using Jaynes' maximum entropy principle to derive prior information, we successively tackle the situations when only the channel delay spread is a priori known, then when it is not known. Exploitation of the time-frequency dimensions are also considered in this framework, to derive the optimal channel estimation associated to some performance measure under any state of knowledge. Simulations corroborate the optimality claim and always prove as good or better in performance than classical estimators.
dc.description15 pages, 11 figures
dc.identifierhttps://arxiv.org/abs/0811.0778
dc.identifierhttp://arxiv.org/abs/0811.0778
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/173271
dc.subjectInformation Theory
dc.subjectProbability
dc.titleA maximum entropy approach to OFDM channel estimation
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