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Abstract

In this paper, we revisit the Recursive Projection-Aggregation (RPA) decoder, of Ye and Abbe (2020), for Reed-Muller (RM) codes. Our main contribution is an explicit upper bound on the probability of incorrect decoding, using the RPA decoder, over a binary symmetric channel (BSC). Importantly, we focus on the events where a single iteration of the RPA decoder, in each recursive call, is sufficient for convergence. Key components of our analysis are explicit estimates of the probability of incorrect decoding of first-order RM codes using a maximum likelihood (ML) decoder, and estimates of the error probabilities during the aggregation phase of the RPA decoder. Our results allow us to show that for RM codes with blocklength \(N = 2^m\), the RPA decoder can achieve vanishing error probabilities, in the large blocklength limit, for RM orders that grow roughly logarithmically in \(m\).

Details

1009240
Identifier / keyword
Title
An Upper Bound on the Error Probability of RPA Decoding of Reed-Muller Codes Over the BSC
Publication title
arXiv.org; Ithaca
Publication year
2024
Publication date
Dec 11, 2024
Section
Computer Science; Mathematics
Publisher
Cornell University Library, arXiv.org
Source
arXiv.org
Place of publication
Ithaca
Country of publication
United States
University/institution
Cornell University Library arXiv.org
e-ISSN
2331-8422
Source type
Working Paper
Language of publication
English
Document type
Working Paper
Publication history
 
 
Online publication date
2024-12-12
Milestone dates
2024-12-11 (Submission v1)
Publication history
 
 
   First posting date
12 Dec 2024
ProQuest document ID
3143450258
Document URL
https://www.proquest.com/working-papers/upper-bound-on-error-probability-rpa-decoding/docview/3143450258/se-2?accountid=208611
Full text outside of ProQuest
Copyright
© 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2024-12-13
Database
ProQuest One Academic