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
Dalam makalah ini, kami mencadangkan kaedah untuk meningkatkan prestasi versi berjujukan algoritma penyahkodan penyebaran kepercayaan (BP), kumpulan merombak algoritma penyahkodan BP untuk kod semakan pariti berketumpatan rendah (LDPC). Algoritma penyahkodan BP yang dipertingkatkan, dipanggil algoritma penyahkodan BP yang dikocok, menyahkod setiap nod simbol dalam siri pada setiap lelaran. Untuk mengurangkan kelewatan penyahkodan algoritma penyahkodan BP yang dikocok, algoritma penyahkodan BP yang dikocok kumpulan membahagikan semua nod simbol kepada beberapa kumpulan. Berbeza dengan kumpulan asal yang dikocok BP, yang secara automatik menjana kumpulan mengikut kedudukan simbol, dalam makalah ini kami mencadangkan kaedah untuk mengumpulkan nod simbol yang menjana kumpulan mengikut struktur graf Tanner bagi kod tersebut. Kaedah yang dicadangkan boleh mempercepatkan penumpuan algoritma BP yang dikocok kumpulan dan memperoleh kadar ralat yang lebih rendah dalam sebilangan kecil lelaran. Kami menunjukkan melalui hasil simulasi bahawa prestasi penyahkodan kaedah yang dicadangkan dipertingkatkan berbanding dengan algoritma penyahkodan BP yang dikocok dan algoritma penyahkod BP yang dikocok kumpulan.
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Salinan
Yoshiyuki SATO, Gou HOSOYA, Hideki YAGI, Shigeichi HIRASAWA, "A Method for Grouping Symbol Nodes of Group Shuffled BP Decoding Algorithm" in IEICE TRANSACTIONS on Fundamentals,
vol. E91-A, no. 10, pp. 2745-2753, October 2008, doi: 10.1093/ietfec/e91-a.10.2745.
Abstract: In this paper, we propose a method for enhancing performance of a sequential version of the belief-propagation (BP) decoding algorithm, the group shuffled BP decoding algorithm for low-density parity-check (LDPC) codes. An improved BP decoding algorithm, called the shuffled BP decoding algorithm, decodes each symbol node in serial at each iteration. To reduce the decoding delay of the shuffled BP decoding algorithm, the group shuffled BP decoding algorithm divides all symbol nodes into several groups. In contrast to the original group shuffled BP, which automatically generates groups according to symbol positions, in this paper we propose a method for grouping symbol nodes which generates groups according to the structure of a Tanner graph of the codes. The proposed method can accelerate the convergence of the group shuffled BP algorithm and obtain a lower error rate in a small number of iterations. We show by simulation results that the decoding performance of the proposed method is improved compared with those of the shuffled BP decoding algorithm and the group shuffled BP decoding algorithm.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1093/ietfec/e91-a.10.2745/_p
Salinan
@ARTICLE{e91-a_10_2745,
author={Yoshiyuki SATO, Gou HOSOYA, Hideki YAGI, Shigeichi HIRASAWA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={A Method for Grouping Symbol Nodes of Group Shuffled BP Decoding Algorithm},
year={2008},
volume={E91-A},
number={10},
pages={2745-2753},
abstract={In this paper, we propose a method for enhancing performance of a sequential version of the belief-propagation (BP) decoding algorithm, the group shuffled BP decoding algorithm for low-density parity-check (LDPC) codes. An improved BP decoding algorithm, called the shuffled BP decoding algorithm, decodes each symbol node in serial at each iteration. To reduce the decoding delay of the shuffled BP decoding algorithm, the group shuffled BP decoding algorithm divides all symbol nodes into several groups. In contrast to the original group shuffled BP, which automatically generates groups according to symbol positions, in this paper we propose a method for grouping symbol nodes which generates groups according to the structure of a Tanner graph of the codes. The proposed method can accelerate the convergence of the group shuffled BP algorithm and obtain a lower error rate in a small number of iterations. We show by simulation results that the decoding performance of the proposed method is improved compared with those of the shuffled BP decoding algorithm and the group shuffled BP decoding algorithm.},
keywords={},
doi={10.1093/ietfec/e91-a.10.2745},
ISSN={1745-1337},
month={October},}
Salinan
TY - JOUR
TI - A Method for Grouping Symbol Nodes of Group Shuffled BP Decoding Algorithm
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2745
EP - 2753
AU - Yoshiyuki SATO
AU - Gou HOSOYA
AU - Hideki YAGI
AU - Shigeichi HIRASAWA
PY - 2008
DO - 10.1093/ietfec/e91-a.10.2745
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E91-A
IS - 10
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - October 2008
AB - In this paper, we propose a method for enhancing performance of a sequential version of the belief-propagation (BP) decoding algorithm, the group shuffled BP decoding algorithm for low-density parity-check (LDPC) codes. An improved BP decoding algorithm, called the shuffled BP decoding algorithm, decodes each symbol node in serial at each iteration. To reduce the decoding delay of the shuffled BP decoding algorithm, the group shuffled BP decoding algorithm divides all symbol nodes into several groups. In contrast to the original group shuffled BP, which automatically generates groups according to symbol positions, in this paper we propose a method for grouping symbol nodes which generates groups according to the structure of a Tanner graph of the codes. The proposed method can accelerate the convergence of the group shuffled BP algorithm and obtain a lower error rate in a small number of iterations. We show by simulation results that the decoding performance of the proposed method is improved compared with those of the shuffled BP decoding algorithm and the group shuffled BP decoding algorithm.
ER -