DocumentCode :
1365415
Title :
Feedback Capacity of Stationary Gaussian Channels
Author :
Kim, Young-Han
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of California, La Jolla, CA, USA
Volume :
56
Issue :
1
fYear :
2010
Firstpage :
57
Lastpage :
85
Abstract :
The feedback capacity of additive stationary Gaussian noise channels is characterized as the solution to a variational problem in the noise power spectral density. When specialized to the first-order autoregressive moving-average noise spectrum, this variational characterization yields a closed-form expression for the feedback capacity. In particular, this result shows that the celebrated Schalkwijk-Kailath coding achieves the feedback capacity for the first-order autoregressive moving-average Gaussian channel, positively answering a long-standing open problem studied by Butman, Tiernan-Schalkwijk, Wolfowitz, Ozarow, Ordentlich, Yang-Kavc¿ic¿-Tatikonda, and others. More generally, it is shown that a k-dimensional generalization of the Schalkwijk-Kailath coding achieves the feedback capacity for any autoregressive moving-average noise spectrum of order k. Simply put, the optimal transmitter iteratively refines the receiver´s knowledge of the intended message. This development reveals intriguing connections between estimation, control, and feedback communication.
Keywords :
Gaussian channels; autoregressive moving average processes; encoding; feedback; Gaussian noise channels; Schalkwijk-Kailath coding; autoregressive moving-average noise spectrum; feedback capacity; feedback communication; first-order autoregressive moving-average noise spectrum; noise power spectral density; optimal transmitter; stationary gaussian channels; Additive noise; Channel capacity; Closed-form solution; Communication system control; Feedback communications; Gaussian channels; Gaussian noise; Gaussian processes; Information theory; Transmitters; Additive Gaussian noise channel; autoregressive moving-average spectrum; channel capacity; feedback; iterative refinement; linear coding; stationary Gaussian process;
fLanguage :
English
Journal_Title :
Information Theory, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9448
Type :
jour
DOI :
10.1109/TIT.2009.2034816
Filename :
5361463
Link To Document :
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