Efficient Maximum Likelihood Decoding of Polar Codes over the Binary Erasure Channel

Yonatan Urman; David Burshtein

doi:10.1109/ISIT45174.2021.9517748

Efficient Maximum Likelihood Decoding of Polar Codes over the Binary Erasure Channel

Yonatan Urman, David Burshtein

School of Electrical Engineering

Tel Aviv University

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

3 Scopus citations

Abstract

A new algorithm for efficient exact maximum likelihood decoding of polar codes (which may be CRC augmented), transmitted over the binary erasure channel, is presented. The algorithm applies a matrix triangulation process on a sparse polar code parity check matrix, followed by solving a small size linear system over GF(2). To implement the matrix triangulation, we apply belief propagation decoding type operations. We also indicate how this decoder can be implemented in parallel for low latency decoding. Numerical simulations are used to evaluate the performance and computational complexity of the new algorithm.

Original language	English
Title of host publication	2021 IEEE International Symposium on Information Theory, ISIT 2021 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1600-1605
Number of pages	6
ISBN (Electronic)	9781538682098
DOIs	https://doi.org/10.1109/ISIT45174.2021.9517748
State	Published - 12 Jul 2021
Event	2021 IEEE International Symposium on Information Theory, ISIT 2021 - Virtual, Melbourne, Australia Duration: 12 Jul 2021 → 20 Jul 2021

Publication series

Name	IEEE International Symposium on Information Theory - Proceedings
Volume	2021-July
ISSN (Print)	2157-8095

Conference

Conference	2021 IEEE International Symposium on Information Theory, ISIT 2021
Country/Territory	Australia
City	Virtual, Melbourne
Period	12/07/21 → 20/07/21

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10.1109/ISIT45174.2021.9517748

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Urman, Y., & Burshtein, D. (2021). Efficient Maximum Likelihood Decoding of Polar Codes over the Binary Erasure Channel. In 2021 IEEE International Symposium on Information Theory, ISIT 2021 - Proceedings (pp. 1600-1605). (IEEE International Symposium on Information Theory - Proceedings; Vol. 2021-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISIT45174.2021.9517748

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abstract = "A new algorithm for efficient exact maximum likelihood decoding of polar codes (which may be CRC augmented), transmitted over the binary erasure channel, is presented. The algorithm applies a matrix triangulation process on a sparse polar code parity check matrix, followed by solving a small size linear system over GF(2). To implement the matrix triangulation, we apply belief propagation decoding type operations. We also indicate how this decoder can be implemented in parallel for low latency decoding. Numerical simulations are used to evaluate the performance and computational complexity of the new algorithm.",

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Urman, Y & Burshtein, D 2021, Efficient Maximum Likelihood Decoding of Polar Codes over the Binary Erasure Channel. in 2021 IEEE International Symposium on Information Theory, ISIT 2021 - Proceedings. IEEE International Symposium on Information Theory - Proceedings, vol. 2021-July, Institute of Electrical and Electronics Engineers Inc., pp. 1600-1605, 2021 IEEE International Symposium on Information Theory, ISIT 2021, Virtual, Melbourne, Australia, 12/07/21. https://doi.org/10.1109/ISIT45174.2021.9517748

Efficient Maximum Likelihood Decoding of Polar Codes over the Binary Erasure Channel. / Urman, Yonatan; Burshtein, David.
2021 IEEE International Symposium on Information Theory, ISIT 2021 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2021. p. 1600-1605 (IEEE International Symposium on Information Theory - Proceedings; Vol. 2021-July).

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

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Urman Y, Burshtein D. Efficient Maximum Likelihood Decoding of Polar Codes over the Binary Erasure Channel. In 2021 IEEE International Symposium on Information Theory, ISIT 2021 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2021. p. 1600-1605. (IEEE International Symposium on Information Theory - Proceedings). doi: 10.1109/ISIT45174.2021.9517748

Efficient Maximum Likelihood Decoding of Polar Codes over the Binary Erasure Channel

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