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Article: Feedback capacity of stationary Gaussian channels further examined

TitleFeedback capacity of stationary Gaussian channels further examined
Authors
KeywordsOptimization
Gaussian processes
Channel capacity
Gaussian noise
Limiting
Issue Date2019
PublisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?puNumber=18
Citation
IEEE Transactions on Information Theory, 2019, v. 65 n. 4, p. 2492-2506 How to Cite?
AbstractIt is well known that the problem of computing the feedback capacity of a stationary Gaussian channel can be recast as an infinite-dimensional optimization problem; moreover, necessary and sufficient conditions for the optimality of a solution to this optimization problem have been characterized, and based on this characterization, an explicit formula for the feedback capacity has been given for the case that the noise is a first-order autoregressive moving-average Gaussian process. In this paper, via a simple “change of variables” trick, we further examine the above-mentioned infinite-dimensional optimization problem. We prove that unless the Gaussian noise is white, its optimal solution is unique, and we propose an algorithm to recursively compute the unique optimal solution, which is guaranteed to converge in theory and features an efficient implementation for a suboptimal solution in practice. Furthermore, for the case, that the noise is a $k$ -th order autoregressive moving-average Gaussian process, we give a relatively more explicit formula for the feedback capacity; more specifically, the feedback capacity is expressed as a simple function evaluated at a solution to a system of polynomial equations.
Persistent Identifierhttp://hdl.handle.net/10722/277449
ISSN
2019 Impact Factor: 3.036
2015 SCImago Journal Rankings: 1.433

 

DC FieldValueLanguage
dc.contributor.authorLiu, T-
dc.contributor.authorHan, G-
dc.date.accessioned2019-09-20T08:51:17Z-
dc.date.available2019-09-20T08:51:17Z-
dc.date.issued2019-
dc.identifier.citationIEEE Transactions on Information Theory, 2019, v. 65 n. 4, p. 2492-2506-
dc.identifier.issn0018-9448-
dc.identifier.urihttp://hdl.handle.net/10722/277449-
dc.description.abstractIt is well known that the problem of computing the feedback capacity of a stationary Gaussian channel can be recast as an infinite-dimensional optimization problem; moreover, necessary and sufficient conditions for the optimality of a solution to this optimization problem have been characterized, and based on this characterization, an explicit formula for the feedback capacity has been given for the case that the noise is a first-order autoregressive moving-average Gaussian process. In this paper, via a simple “change of variables” trick, we further examine the above-mentioned infinite-dimensional optimization problem. We prove that unless the Gaussian noise is white, its optimal solution is unique, and we propose an algorithm to recursively compute the unique optimal solution, which is guaranteed to converge in theory and features an efficient implementation for a suboptimal solution in practice. Furthermore, for the case, that the noise is a $k$ -th order autoregressive moving-average Gaussian process, we give a relatively more explicit formula for the feedback capacity; more specifically, the feedback capacity is expressed as a simple function evaluated at a solution to a system of polynomial equations.-
dc.languageeng-
dc.publisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?puNumber=18-
dc.relation.ispartofIEEE Transactions on Information Theory-
dc.rightsIEEE Transactions on Information Theory. Copyright © IEEE.-
dc.rights©20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.-
dc.subjectOptimization-
dc.subjectGaussian processes-
dc.subjectChannel capacity-
dc.subjectGaussian noise-
dc.subjectLimiting-
dc.titleFeedback capacity of stationary Gaussian channels further examined-
dc.typeArticle-
dc.identifier.emailHan, G: ghan@hku.hk-
dc.identifier.authorityHan, G=rp00702-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/TIT.2018.2876897-
dc.identifier.scopuseid_2-s2.0-85055208767-
dc.identifier.hkuros305685-
dc.identifier.volume65-
dc.identifier.issue4-
dc.identifier.spage2492-
dc.identifier.epage2506-
dc.publisher.placeUnited States-

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