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Conference Paper: Feedback Capacity of Stationary Gaussian Channels Further Examined
Title  Feedback Capacity of Stationary Gaussian Channels Further Examined 

Authors  
Issue Date  2018 
Citation  2018 Information Theory and Applications Workshop, San Diego, USA, 1116 February 2018 How to Cite? 
Abstract  It is well known that the problem of computing the feedback capacity of a stationary Gaussian channel can be recast as an infinitedimensional 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 firstorder autoregressive movingaverage Gaussian process. In this paper, we further
examine the abovementioned infinitedimensional 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 kth order autoregressive movingaverage 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, which is amenable to numerical computation for the cases k = 1,2 and possibly beyond. 
Description  Session: Channel Capacity 1 
Persistent Identifier  http://hdl.handle.net/10722/279676 
DC Field  Value  Language 

dc.contributor.author  Han, G   
dc.contributor.author  Liu, T   
dc.date.accessioned  20191128T06:21:09Z   
dc.date.available  20191128T06:21:09Z   
dc.date.issued  2018   
dc.identifier.citation  2018 Information Theory and Applications Workshop, San Diego, USA, 1116 February 2018   
dc.identifier.uri  http://hdl.handle.net/10722/279676   
dc.description  Session: Channel Capacity 1   
dc.description.abstract  It is well known that the problem of computing the feedback capacity of a stationary Gaussian channel can be recast as an infinitedimensional 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 firstorder autoregressive movingaverage Gaussian process. In this paper, we further examine the abovementioned infinitedimensional 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 kth order autoregressive movingaverage 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, which is amenable to numerical computation for the cases k = 1,2 and possibly beyond.   
dc.language  eng   
dc.relation.ispartof  The 2018 Information Theory and Applications Workshop   
dc.title  Feedback Capacity of Stationary Gaussian Channels Further Examined   
dc.type  Conference_Paper   
dc.identifier.email  Han, G: ghan@hku.hk   
dc.identifier.authority  Han, G=rp00702   
dc.identifier.hkuros  305692   