The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
ADMM(교대 방향 승수 방법)을 기반으로 하는 LP(선형 프로그래밍) 디코딩은 LDPC(저밀도 패리티 검사) 코드에 효과적인 것으로 입증되었습니다. 그러나 HDPC(고밀도 패리티 검사) 코드의 경우 ADMM-LP 디코더는 HDPC 코드의 고밀도 검사 행렬과 HDPC 코드의 기본 폴리토프에 있는 수많은 의사 코드워드라는 두 가지 문제에 직면합니다. 전자의 문제는 체크 폴리토프 투영을 극도로 복잡하게 만들고, 후자의 문제는 프레임 오류율(FER) 성능을 저하시킵니다. 이러한 문제를 해결하기 위해 HDPC-EVA라는 HDPC 코드용 ADMM-LP 디코딩 알고리즘에 EVA(짝수 정점 알고리즘)를 도입했습니다. HDPC-EVA는 프로젝션 프로세스의 복잡성을 줄이고 FER 성능을 향상시킬 수 있습니다. 우리는 코드의 자동형성 그룹을 통해 제안된 디코더를 더욱 향상시켜 패리티 검사 매트릭스에 다양성을 생성합니다. 시뮬레이션 결과는 제안된 디코더가 각 반복의 평균 디코딩 시간을 30%-60%까지 줄일 수 있을 뿐만 아니라 일부 BCH 코드에서 거의 최대 우도(ML) 성능을 달성할 수 있음을 보여줍니다.
Yujin ZHENG
Central China Normal University
Yan LIN
Central China Normal University
Zhuo ZHANG
Shanghai Aerospace Electronic Technology Institute
Qinglin ZHANG
Central China Normal University
Qiaoqiao XIA
Central China Normal University
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부
Yujin ZHENG, Yan LIN, Zhuo ZHANG, Qinglin ZHANG, Qiaoqiao XIA, "An Enhanced HDPC-EVA Decoder Based on ADMM" in IEICE TRANSACTIONS on Fundamentals,
vol. E104-A, no. 10, pp. 1425-1429, October 2021, doi: 10.1587/transfun.2020EAL2116.
Abstract: Linear programming (LP) decoding based on the alternating direction method of multipliers (ADMM) has proved to be effective for low-density parity-check (LDPC) codes. However, for high-density parity-check (HDPC) codes, the ADMM-LP decoder encounters two problems, namely a high-density check matrix in HDPC codes and a great number of pseudocodewords in HDPC codes' fundamental polytope. The former problem makes the check polytope projection extremely complex, and the latter one leads to poor frame error rates (FER) performance. To address these issues, we introduce the even vertex algorithm (EVA) into the ADMM-LP decoding algorithm for HDPC codes, named as HDPC-EVA. HDPC-EVA can reduce the complexity of the projection process and improve the FER performance. We further enhance the proposed decoder by the automorphism groups of codes, creating diversity in the parity-check matrix. The simulation results show that the proposed decoder is capable of cutting down the average decoding time for each iteration by 30%-60%, as well as achieving near maximum likelihood (ML) performance on some BCH codes.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.2020EAL2116/_p
부
@ARTICLE{e104-a_10_1425,
author={Yujin ZHENG, Yan LIN, Zhuo ZHANG, Qinglin ZHANG, Qiaoqiao XIA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={An Enhanced HDPC-EVA Decoder Based on ADMM},
year={2021},
volume={E104-A},
number={10},
pages={1425-1429},
abstract={Linear programming (LP) decoding based on the alternating direction method of multipliers (ADMM) has proved to be effective for low-density parity-check (LDPC) codes. However, for high-density parity-check (HDPC) codes, the ADMM-LP decoder encounters two problems, namely a high-density check matrix in HDPC codes and a great number of pseudocodewords in HDPC codes' fundamental polytope. The former problem makes the check polytope projection extremely complex, and the latter one leads to poor frame error rates (FER) performance. To address these issues, we introduce the even vertex algorithm (EVA) into the ADMM-LP decoding algorithm for HDPC codes, named as HDPC-EVA. HDPC-EVA can reduce the complexity of the projection process and improve the FER performance. We further enhance the proposed decoder by the automorphism groups of codes, creating diversity in the parity-check matrix. The simulation results show that the proposed decoder is capable of cutting down the average decoding time for each iteration by 30%-60%, as well as achieving near maximum likelihood (ML) performance on some BCH codes.},
keywords={},
doi={10.1587/transfun.2020EAL2116},
ISSN={1745-1337},
month={October},}
부
TY - JOUR
TI - An Enhanced HDPC-EVA Decoder Based on ADMM
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1425
EP - 1429
AU - Yujin ZHENG
AU - Yan LIN
AU - Zhuo ZHANG
AU - Qinglin ZHANG
AU - Qiaoqiao XIA
PY - 2021
DO - 10.1587/transfun.2020EAL2116
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E104-A
IS - 10
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - October 2021
AB - Linear programming (LP) decoding based on the alternating direction method of multipliers (ADMM) has proved to be effective for low-density parity-check (LDPC) codes. However, for high-density parity-check (HDPC) codes, the ADMM-LP decoder encounters two problems, namely a high-density check matrix in HDPC codes and a great number of pseudocodewords in HDPC codes' fundamental polytope. The former problem makes the check polytope projection extremely complex, and the latter one leads to poor frame error rates (FER) performance. To address these issues, we introduce the even vertex algorithm (EVA) into the ADMM-LP decoding algorithm for HDPC codes, named as HDPC-EVA. HDPC-EVA can reduce the complexity of the projection process and improve the FER performance. We further enhance the proposed decoder by the automorphism groups of codes, creating diversity in the parity-check matrix. The simulation results show that the proposed decoder is capable of cutting down the average decoding time for each iteration by 30%-60%, as well as achieving near maximum likelihood (ML) performance on some BCH codes.
ER -