Large-Small Sorting for Successive Cancellation List Decoding of Polar Codes

The successive cancellation list (SCL) decoding is used to achieve good error-correcting performance for practical finite-length polar codes. However, the metric sorting that is repeatedly performed in SCL decoding increases the overall decoding latency as the list size increases, making it difficul...

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Main Authors: Kyungpil Lee, In-Cheol Park
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9097261/
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spelling doaj-50bb08c0edc246a1ae184cae9ebce1312021-03-30T02:18:25ZengIEEEIEEE Access2169-35362020-01-018969559696210.1109/ACCESS.2020.29960169097261Large-Small Sorting for Successive Cancellation List Decoding of Polar CodesKyungpil Lee0https://orcid.org/0000-0002-8221-0655In-Cheol Park1https://orcid.org/0000-0003-3524-2838School of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South KoreaSchool of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, South KoreaThe successive cancellation list (SCL) decoding is used to achieve good error-correcting performance for practical finite-length polar codes. However, the metric sorting that is repeatedly performed in SCL decoding increases the overall decoding latency as the list size increases, making it difficult to apply the SCL decoding to the applications with limited processing time. To reduce the latency of the metric sorting, this paper proposes a new sorting method derived by analyzing path extension cases encountered in SCL decoding. The proposed method can avoid unnecessary sorting operations by adaptively determining the sorting size, and can be combined with other metric sorting methods. Simulation results show that the proposed method significantly reduces the decoding latency for various list sizes and code rates without degrading the error-correcting performance. The proposed method also becomes more effective as the code rate or the list size increases. Combined with the state-of-the-art sorting method, the proposed method reduces the average SCL decoding latency for a (1024, 512) polar code by 33.1% when the list size is 8.https://ieeexplore.ieee.org/document/9097261/Polar codessuccessive cancellation list decodingmetric sortinglarge-small sortinglow latency
collection DOAJ
language English
format Article
sources DOAJ
author Kyungpil Lee
In-Cheol Park
spellingShingle Kyungpil Lee
In-Cheol Park
Large-Small Sorting for Successive Cancellation List Decoding of Polar Codes
IEEE Access
Polar codes
successive cancellation list decoding
metric sorting
large-small sorting
low latency
author_facet Kyungpil Lee
In-Cheol Park
author_sort Kyungpil Lee
title Large-Small Sorting for Successive Cancellation List Decoding of Polar Codes
title_short Large-Small Sorting for Successive Cancellation List Decoding of Polar Codes
title_full Large-Small Sorting for Successive Cancellation List Decoding of Polar Codes
title_fullStr Large-Small Sorting for Successive Cancellation List Decoding of Polar Codes
title_full_unstemmed Large-Small Sorting for Successive Cancellation List Decoding of Polar Codes
title_sort large-small sorting for successive cancellation list decoding of polar codes
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2020-01-01
description The successive cancellation list (SCL) decoding is used to achieve good error-correcting performance for practical finite-length polar codes. However, the metric sorting that is repeatedly performed in SCL decoding increases the overall decoding latency as the list size increases, making it difficult to apply the SCL decoding to the applications with limited processing time. To reduce the latency of the metric sorting, this paper proposes a new sorting method derived by analyzing path extension cases encountered in SCL decoding. The proposed method can avoid unnecessary sorting operations by adaptively determining the sorting size, and can be combined with other metric sorting methods. Simulation results show that the proposed method significantly reduces the decoding latency for various list sizes and code rates without degrading the error-correcting performance. The proposed method also becomes more effective as the code rate or the list size increases. Combined with the state-of-the-art sorting method, the proposed method reduces the average SCL decoding latency for a (1024, 512) polar code by 33.1% when the list size is 8.
topic Polar codes
successive cancellation list decoding
metric sorting
large-small sorting
low latency
url https://ieeexplore.ieee.org/document/9097261/
work_keys_str_mv AT kyungpillee largesmallsortingforsuccessivecancellationlistdecodingofpolarcodes
AT incheolpark largesmallsortingforsuccessivecancellationlistdecodingofpolarcodes
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