2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information

2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information
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Paper Detail

Paper IDSS-8.4
Paper Title TOWARDS PRACTICAL NEAR-MAXIMUM-LIKELIHOOD DECODING OF ERROR-CORRECTING CODES: AN OVERVIEW
Authors Thibaud Tonnellier, McGill University, Canada; Marzieh Hashemipour-Nazari, Eindhoven University of Technology, Netherlands; Nghia Doan, Warren Gross, McGill University, Canada; Alexios Balatsoukas-Stimming, Eindhoven University of Technology, Netherlands
SessionSS-8: Near-ML Decoding of Error-correcting Codes: Algorithms and Implementation
LocationGather.Town
Session Time:Wednesday, 09 June, 16:30 - 17:15
Presentation Time:Wednesday, 09 June, 16:30 - 17:15
Presentation Poster
Topic Special Sessions: Near-ML Decoding of Error-correcting Codes: Algorithms and Implementation
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract While in the past several decades the trend to go towards increasing error-correcting code lengths was predominant to get closer to the Shannon limit, applications that require short block length are developing. Therefore, decoding techniques that can achieve near-maximum-likelihood (near-ML) are gaining momentum. This overview paper surveys recent progress in this emerging field by reviewing the GRAND algorithm, linear programming decoding, machine-learning aided decoding and the recursive projection-aggregation decoding algorithm. For each of the decoding algorithms, both algorithmic and hardware implementations are considered, and future research directions are outlined.