Maximum Likelihood Decoding for Channels with Uniform Noise and Signal Dependent Offset

Renfei Bu; Jos H. Weber; Kees A. Schouhamer Immink

doi:10.1109/ISIT44484.2020.9174270

Maximum Likelihood Decoding for Channels with Uniform Noise and Signal Dependent Offset

Renfei Bu, Jos H. Weber, Kees A. Schouhamer Immink

Discrete Mathematics and Optimization

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

1 Citation (Scopus)

Abstract

Maximum likelihood (ML) decision criteria have been developed for channels suffering from signal independent offset mismatch. Here, such criteria are considered for signal dependent offset, which means that the value of the offset may differ for distinct signal levels rather than being the same for all levels. An ML decision criterion is derived, assuming uniform distributions for both the noise and the offset. In particular, for the proposed ML decoder, bounds are determined on the standard deviations of the noise and the offset which lead to a word error rate equal to zero. Simulation results are presented confirming the findings.

Original language	English
Title of host publication	2020 IEEE International Symposium on Information Theory (ISIT)
Subtitle of host publication	Proceedings
Place of Publication	Piscataway
Publisher	IEEE
Pages	706-710
Number of pages	5
ISBN (Electronic)	978-1-7281-6432-8
ISBN (Print)	978-1-7281-6433-5
DOIs	https://doi.org/10.1109/ISIT44484.2020.9174270
Publication status	Published - 2020
Event	2020 IEEE International Symposium on Information Theory, ISIT 2020 - Los Angeles, United States Duration: 21 Jul 2020 → 26 Jul 2020

Conference

Conference	2020 IEEE International Symposium on Information Theory, ISIT 2020
Country/Territory	United States
City	Los Angeles
Period	21/07/20 → 26/07/20

Keywords

Maximum likelihood decoding
offset mismatch
signal dependent offset

Access to Document

10.1109/ISIT44484.2020.9174270

Cite this

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title = "Maximum Likelihood Decoding for Channels with Uniform Noise and Signal Dependent Offset",

abstract = "Maximum likelihood (ML) decision criteria have been developed for channels suffering from signal independent offset mismatch. Here, such criteria are considered for signal dependent offset, which means that the value of the offset may differ for distinct signal levels rather than being the same for all levels. An ML decision criterion is derived, assuming uniform distributions for both the noise and the offset. In particular, for the proposed ML decoder, bounds are determined on the standard deviations of the noise and the offset which lead to a word error rate equal to zero. Simulation results are presented confirming the findings.",

keywords = "Maximum likelihood decoding, offset mismatch, signal dependent offset",

author = "Renfei Bu and Weber, {Jos H.} and {Schouhamer Immink}, {Kees A.}",

year = "2020",

doi = "10.1109/ISIT44484.2020.9174270",

language = "English",

isbn = "978-1-7281-6433-5",

pages = "706--710",

booktitle = "2020 IEEE International Symposium on Information Theory (ISIT)",

publisher = "IEEE",

address = "United States",

note = "2020 IEEE International Symposium on Information Theory, ISIT 2020 ; Conference date: 21-07-2020 Through 26-07-2020",

}

Bu, R, Weber, JH & Schouhamer Immink, KA 2020, Maximum Likelihood Decoding for Channels with Uniform Noise and Signal Dependent Offset. in 2020 IEEE International Symposium on Information Theory (ISIT): Proceedings., 9174270, IEEE, Piscataway, pp. 706-710, 2020 IEEE International Symposium on Information Theory, ISIT 2020, Los Angeles, United States, 21/07/20. https://doi.org/10.1109/ISIT44484.2020.9174270

Maximum Likelihood Decoding for Channels with Uniform Noise and Signal Dependent Offset. / Bu, Renfei; Weber, Jos H.; Schouhamer Immink, Kees A.
2020 IEEE International Symposium on Information Theory (ISIT): Proceedings. Piscataway: IEEE, 2020. p. 706-710 9174270.

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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PY - 2020

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N2 - Maximum likelihood (ML) decision criteria have been developed for channels suffering from signal independent offset mismatch. Here, such criteria are considered for signal dependent offset, which means that the value of the offset may differ for distinct signal levels rather than being the same for all levels. An ML decision criterion is derived, assuming uniform distributions for both the noise and the offset. In particular, for the proposed ML decoder, bounds are determined on the standard deviations of the noise and the offset which lead to a word error rate equal to zero. Simulation results are presented confirming the findings.

AB - Maximum likelihood (ML) decision criteria have been developed for channels suffering from signal independent offset mismatch. Here, such criteria are considered for signal dependent offset, which means that the value of the offset may differ for distinct signal levels rather than being the same for all levels. An ML decision criterion is derived, assuming uniform distributions for both the noise and the offset. In particular, for the proposed ML decoder, bounds are determined on the standard deviations of the noise and the offset which lead to a word error rate equal to zero. Simulation results are presented confirming the findings.

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DO - 10.1109/ISIT44484.2020.9174270

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T2 - 2020 IEEE International Symposium on Information Theory, ISIT 2020

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ER -

Maximum Likelihood Decoding for Channels with Uniform Noise and Signal Dependent Offset

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