Finding the best mismatched detector for channel coding and hypothesis testing

Emmanuel Abbe; Muriel Médard; Sean Meyn; Lizhong Zheng

doi:10.1109/ITA.2007.4357593

Finding the best mismatched detector for channel coding and hypothesis testing

Emmanuel Abbe, Muriel Médard, Sean Meyn, Lizhong Zheng

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

6 Scopus citations

Abstract

The mismatched-channel formulation is generalized to obtain simplified algorithms for computation of capacity bounds and improved signal constellation designs. The following issues are addressed: (i) For a given finite dimensional family of linear detectors, how can we compute the best in this class to maximize the reliably received rate? That is, what is the best mismatched detector in a given class? (ii) For computation of the best detector, a new algorithm is proposed based on a stochastic approximation implementation of the Newton-Raphson method. (iii) The geometric setting provides a unified treatment of channel coding and robust/adaptive hypothesis testing.

Original language	English (US)
Title of host publication	2007 Information Theory and Applications Workshop, Conference Proceedings, ITA
Pages	284-288
Number of pages	5
DOIs	https://doi.org/10.1109/ITA.2007.4357593
State	Published - Dec 1 2007
Externally published	Yes
Event	2007 Information Theory and Applications Workshop, ITA - San Diego, CA, United States Duration: Jan 29 2007 → Feb 2 2007

Publication series

Name	2007 Information Theory and Applications Workshop, Conference Proceedings, ITA

Other

Other	2007 Information Theory and Applications Workshop, ITA
Country/Territory	United States
City	San Diego, CA
Period	1/29/07 → 2/2/07

All Science Journal Classification (ASJC) codes

Information Systems
Information Systems and Management

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10.1109/ITA.2007.4357593

Cite this

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title = "Finding the best mismatched detector for channel coding and hypothesis testing",

abstract = "The mismatched-channel formulation is generalized to obtain simplified algorithms for computation of capacity bounds and improved signal constellation designs. The following issues are addressed: (i) For a given finite dimensional family of linear detectors, how can we compute the best in this class to maximize the reliably received rate? That is, what is the best mismatched detector in a given class? (ii) For computation of the best detector, a new algorithm is proposed based on a stochastic approximation implementation of the Newton-Raphson method. (iii) The geometric setting provides a unified treatment of channel coding and robust/adaptive hypothesis testing.",

author = "Emmanuel Abbe and Muriel M{\'e}dard and Sean Meyn and Lizhong Zheng",

year = "2007",

month = dec,

day = "1",

doi = "10.1109/ITA.2007.4357593",

language = "English (US)",

isbn = "9780615153148",

series = "2007 Information Theory and Applications Workshop, Conference Proceedings, ITA",

pages = "284--288",

booktitle = "2007 Information Theory and Applications Workshop, Conference Proceedings, ITA",

note = "2007 Information Theory and Applications Workshop, ITA ; Conference date: 29-01-2007 Through 02-02-2007",

}

Abbe, E, Médard, M, Meyn, S & Zheng, L 2007, Finding the best mismatched detector for channel coding and hypothesis testing. in 2007 Information Theory and Applications Workshop, Conference Proceedings, ITA., 4357593, 2007 Information Theory and Applications Workshop, Conference Proceedings, ITA, pp. 284-288, 2007 Information Theory and Applications Workshop, ITA, San Diego, CA, United States, 1/29/07. https://doi.org/10.1109/ITA.2007.4357593

Finding the best mismatched detector for channel coding and hypothesis testing. / Abbe, Emmanuel; Médard, Muriel; Meyn, Sean et al.
2007 Information Theory and Applications Workshop, Conference Proceedings, ITA. 2007. p. 284-288 4357593 (2007 Information Theory and Applications Workshop, Conference Proceedings, ITA).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Finding the best mismatched detector for channel coding and hypothesis testing

AU - Abbe, Emmanuel

AU - Médard, Muriel

AU - Meyn, Sean

AU - Zheng, Lizhong

PY - 2007/12/1

Y1 - 2007/12/1

N2 - The mismatched-channel formulation is generalized to obtain simplified algorithms for computation of capacity bounds and improved signal constellation designs. The following issues are addressed: (i) For a given finite dimensional family of linear detectors, how can we compute the best in this class to maximize the reliably received rate? That is, what is the best mismatched detector in a given class? (ii) For computation of the best detector, a new algorithm is proposed based on a stochastic approximation implementation of the Newton-Raphson method. (iii) The geometric setting provides a unified treatment of channel coding and robust/adaptive hypothesis testing.

AB - The mismatched-channel formulation is generalized to obtain simplified algorithms for computation of capacity bounds and improved signal constellation designs. The following issues are addressed: (i) For a given finite dimensional family of linear detectors, how can we compute the best in this class to maximize the reliably received rate? That is, what is the best mismatched detector in a given class? (ii) For computation of the best detector, a new algorithm is proposed based on a stochastic approximation implementation of the Newton-Raphson method. (iii) The geometric setting provides a unified treatment of channel coding and robust/adaptive hypothesis testing.

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BT - 2007 Information Theory and Applications Workshop, Conference Proceedings, ITA

T2 - 2007 Information Theory and Applications Workshop, ITA

Y2 - 29 January 2007 through 2 February 2007

ER -

Finding the best mismatched detector for channel coding and hypothesis testing

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All Science Journal Classification (ASJC) codes

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