Reduced Complexity RPA Decoder for Reed-Muller Codes

Jiajie Li; Syed Mohsin Abbas; Thibaud Tonnellier; Warren J. Gross

doi:10.1109/ISTC49272.2021.9594060

Reduced Complexity RPA Decoder for Reed-Muller Codes

Jiajie Li, Syed Mohsin Abbas, Thibaud Tonnellier, Warren J. Gross

Research output: Chapter in Book/Conference Proceeding/Report › Conference Paper published in a book › peer-review

11 Citations (Scopus)

Abstract

The recursive projection-aggregation (RPA) decoder is a recently proposed near maximum likelihood (ML) decoder for Reed-Muller (RM) codes with low rates and short code lengths. However, the high computational complexity of RPA decoding is a major bottleneck for using RPA in applications that have a limited resource and energy budget. In this work, syndrome-based early stopping techniques as well as a scheduling scheme are proposed for the RPA decoder, which help in reducing the computational complexity while keeping similar decoding performance. Comparing to the baseline RPA decoder, the proposed techniques result in a 69-98% reduction in the average computational complexity for a target frame error rate (FER) of 10-5. Additionally, this work introduces hardware-friendly approximation functions to replace the RPA's computationally expensive transcendental projection function.

Original language	English
Title of host publication	2021 11th International Symposium on Topics in Coding, ISTC 2021
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781665409438
DOIs	https://doi.org/10.1109/ISTC49272.2021.9594060
Publication status	Published - 2021
Externally published	Yes
Event	11th International Symposium on Topics in Coding, ISTC 2021 - Montreal, Canada Duration: 30 Aug 2021 → 3 Sept 2021

Publication series

Name	2021 11th International Symposium on Topics in Coding, ISTC 2021

Conference

Conference	11th International Symposium on Topics in Coding, ISTC 2021
Country/Territory	Canada
City	Montreal
Period	30/08/21 → 3/09/21

Bibliographical note

Publisher Copyright:
© 2021 IEEE.

Keywords

Early stopping criteria
Maximum likelihood (ML) decoding
Recursive projection-aggregation (RPA) decoder
Reed-Muller codes
Short codes

Access to Document

10.1109/ISTC49272.2021.9594060

Cite this

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title = "Reduced Complexity RPA Decoder for Reed-Muller Codes",

abstract = "The recursive projection-aggregation (RPA) decoder is a recently proposed near maximum likelihood (ML) decoder for Reed-Muller (RM) codes with low rates and short code lengths. However, the high computational complexity of RPA decoding is a major bottleneck for using RPA in applications that have a limited resource and energy budget. In this work, syndrome-based early stopping techniques as well as a scheduling scheme are proposed for the RPA decoder, which help in reducing the computational complexity while keeping similar decoding performance. Comparing to the baseline RPA decoder, the proposed techniques result in a 69-98\% reduction in the average computational complexity for a target frame error rate (FER) of 10-5. Additionally, this work introduces hardware-friendly approximation functions to replace the RPA's computationally expensive transcendental projection function.",

keywords = "Early stopping criteria, Maximum likelihood (ML) decoding, Recursive projection-aggregation (RPA) decoder, Reed-Muller codes, Short codes",

author = "Jiajie Li and Abbas, \{Syed Mohsin\} and Thibaud Tonnellier and Gross, \{Warren J.\}",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 11th International Symposium on Topics in Coding, ISTC 2021 ; Conference date: 30-08-2021 Through 03-09-2021",

year = "2021",

doi = "10.1109/ISTC49272.2021.9594060",

language = "English",

series = "2021 11th International Symposium on Topics in Coding, ISTC 2021",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2021 11th International Symposium on Topics in Coding, ISTC 2021",

}

Li, J, Abbas, SM, Tonnellier, T & Gross, WJ 2021, Reduced Complexity RPA Decoder for Reed-Muller Codes. in 2021 11th International Symposium on Topics in Coding, ISTC 2021. 2021 11th International Symposium on Topics in Coding, ISTC 2021, Institute of Electrical and Electronics Engineers Inc., 11th International Symposium on Topics in Coding, ISTC 2021, Montreal, Canada, 30/08/21. https://doi.org/10.1109/ISTC49272.2021.9594060

Reduced Complexity RPA Decoder for Reed-Muller Codes. / Li, Jiajie; Abbas, Syed Mohsin; Tonnellier, Thibaud et al.
2021 11th International Symposium on Topics in Coding, ISTC 2021. Institute of Electrical and Electronics Engineers Inc., 2021. (2021 11th International Symposium on Topics in Coding, ISTC 2021).

Research output: Chapter in Book/Conference Proceeding/Report › Conference Paper published in a book › peer-review

TY - GEN

T1 - Reduced Complexity RPA Decoder for Reed-Muller Codes

AU - Li, Jiajie

AU - Abbas, Syed Mohsin

AU - Tonnellier, Thibaud

AU - Gross, Warren J.

PY - 2021

Y1 - 2021

N2 - The recursive projection-aggregation (RPA) decoder is a recently proposed near maximum likelihood (ML) decoder for Reed-Muller (RM) codes with low rates and short code lengths. However, the high computational complexity of RPA decoding is a major bottleneck for using RPA in applications that have a limited resource and energy budget. In this work, syndrome-based early stopping techniques as well as a scheduling scheme are proposed for the RPA decoder, which help in reducing the computational complexity while keeping similar decoding performance. Comparing to the baseline RPA decoder, the proposed techniques result in a 69-98% reduction in the average computational complexity for a target frame error rate (FER) of 10-5. Additionally, this work introduces hardware-friendly approximation functions to replace the RPA's computationally expensive transcendental projection function.

AB - The recursive projection-aggregation (RPA) decoder is a recently proposed near maximum likelihood (ML) decoder for Reed-Muller (RM) codes with low rates and short code lengths. However, the high computational complexity of RPA decoding is a major bottleneck for using RPA in applications that have a limited resource and energy budget. In this work, syndrome-based early stopping techniques as well as a scheduling scheme are proposed for the RPA decoder, which help in reducing the computational complexity while keeping similar decoding performance. Comparing to the baseline RPA decoder, the proposed techniques result in a 69-98% reduction in the average computational complexity for a target frame error rate (FER) of 10-5. Additionally, this work introduces hardware-friendly approximation functions to replace the RPA's computationally expensive transcendental projection function.

KW - Early stopping criteria

KW - Maximum likelihood (ML) decoding

KW - Recursive projection-aggregation (RPA) decoder

KW - Reed-Muller codes

KW - Short codes

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BT - 2021 11th International Symposium on Topics in Coding, ISTC 2021

PB - Institute of Electrical and Electronics Engineers Inc.

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ER -

Reduced Complexity RPA Decoder for Reed-Muller Codes

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Keywords

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