Restart Mechanisms for the Successive-Cancellation List-Flip Decoding of Polar Codes

Polar codes concatenated with a cyclic redundancy check (CRC) code have been selected in the 5G standard with the successive-cancellation list (SCL) of list size L = 8 as the baseline algorithm. Despite providing great error-correction performance, a large list size increases the hardware complexity of the SCL decoder. Alternatively, flip decoding algorithms were proposed to improve the error-correction performance with a low-complexity hardware implementation. The combination of list and flip algorithms, the successive-cancellation list flip (SCLF) and dynamic SCLF (DSCLF) algorithms, provides error-correction performance close to SCL-32 with a list size L = 2 and Tmax = 300 maximum additional trials. However, these decoders have a variable execution time, a characteristic that poses a challenge to some practical applications. In this work, we propose a restart mechanism for list-flip algorithms that allows us to skip parts of the decoding computations without affecting the error-correction performance. We show that the restart location cannot realistically be allowed to occur at any location in a codeword as it would lead to an unreasonable memory overhead under DSCLF. Hence, we propose a mechanism where the possible restart locations are limited to a set and propose various construction methods for that set. The construction methods are compared, and the tradeoffs are discussed. For a polar code of length N = 1024 and rate ¼, under DSCLF decoding with a list size L = 2 and a maximum number of trials Tmax = 300, our proposed approach is shown to reduce the average execution time by 41.7% with four restart locations at the cost of approximately 1.5% in memory overhead.

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Publication Details

Journal
Entropy
Published
2025-03-14
DOI
https://doi.org/10.3390/e27030309
Citations
2
Primary Topic
Error Correcting Code Techniques
Type
article
Field-Weighted Citation Impact
2.97

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article

Restart Mechanisms for the Successive-Cancellation List-Flip Decoding of Polar Codes

Pascal Giard, Charles Pillet, Alexios Balatsoukas‐Stimming, Ilshat Sagitov
2 citations
Entropy
Error Correcting Code Techniques
2.97
article

Restart Mechanisms for the Successive-Cancellation List-Flip Decoding of Polar Codes

Pascal Giard, Charles Pillet, Alexios Balatsoukas‐Stimming, Ilshat Sagitov
article en
2 citations

Abstract

Polar codes concatenated with a cyclic redundancy check (CRC) code have been selected in the 5G standard with the successive-cancellation list (SCL) of list size L = 8 as the baseline algorithm. Despite providing great error-correction performance, a large list size increases the hardware complexity of the SCL decoder. Alternatively, flip decoding algorithms were proposed to improve the error-correction performance with a low-complexity hardware implementation. The combination of list and flip algorithms, the successive-cancellation list flip (SCLF) and dynamic SCLF (DSCLF) algorithms, provides error-correction performance close to SCL-32 with a list size L = 2 and Tmax = 300 maximum additional trials. However, these decoders have a variable execution time, a characteristic that poses a challenge to some practical applications. In this work, we propose a restart mechanism for list-flip algorithms that allows us to skip parts of the decoding computations without affecting the error-correction performance. We show that the restart location cannot realistically be allowed to occur at any location in a codeword as it would lead to an unreasonable memory overhead under DSCLF. Hence, we propose a mechanism where the possible restart locations are limited to a set and propose various construction methods for that set. The construction methods are compared, and the tradeoffs are discussed. For a polar code of length N = 1024 and rate ¼, under DSCLF decoding with a list size L = 2 and a maximum number of trials Tmax = 300, our proposed approach is shown to reduce the average execution time by 41.7% with four restart locations at the cost of approximately 1.5% in memory overhead.

EntropyVol. 27(3)
Eindhoven University of Technology (NL), École de Technologie Supérieure (CA)
Natural Sciences and Engineering Research Council of Canada
Openalex Percentile: Top 10%
Error Correcting Code Techniques
2.97
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