Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences

On the Probabilistic Computation Method with Reliability for the Weight Distribution of LDPC Codes

Masanori Hirotomo, Masami Mohri, Masakatu Morii

Published Jan 1, 2012• 1 citation
Publisher

Abstract

In the analysis of maximum-likelihood decoding performance of low-density parity-check (LDPC) codes, the weight distribution is an important factor. We presented a probabilistic method for computing the weight distribution of LDPC codes, and showed results of computing the weight distribution of several LDPC codes. In this paper, we improve our previously presented method and propose a probabilistic computation method with reliability for the weight distribution of LDPC codes. Using the proposed method, we can determine the weight distribution with small failure probability.

DOI
10.1587/transfun.e95.a.790

Related papers

A reliability-based computation method for the weight distribution of LDPC codes using the probabilistic algorithm

Masanori Hirotomo, Masami Mohri, Masakatu Morii

In the analysis of maximum-likelihood decoding performance of low-density parity-check (LDPC) codes, the weight distribution is an important factor. Some methods based on the error impluse method have presented in order to estimate the weight distribution of LDPC codes. However, these methods have no scheme which determine the number of codeword in LDPC codes. In this paper, we propose a reliability-based computation method for the weight distribution of LDPC codes using the probabilistic algorithm. Using the proposed method, we can determine the weight distribution of LDPC codes with small failure probability.

IEEE International Symposium on Information Theory (ISIT)•Jul 1, 2011•0 citations

A probabilistic computation method for the weight distribution of low-density parity-check codes

Masanori Hirotomo, Masami Mohri, Masakatu Morii

Low-density parity-check (LDPC) codes achieve outstanding performance by the sum-product decoder. Its performance approaches the maximum-likelihood (ML) decoding performance at high SNR region. Upper bounds on the error probability of the ML decoded LDPC codes can be computed using the weight distribution. Recently, X.-Y. Hu et al. presented an approximate algorithm for estimating the weight distribution of LDPC codes. However, the weight distribution computed by their method depends on the iterative decoding algorithm, and is not always estimated exactly. In this paper, we propose a probabilistic method for computing the low-part weight distribution of LDPC codes. Using our method, the approximate weight distribution of LDPC codes can be computed with high accuracy

IEEE International Symposium on Information Theory (ISIT)•Jan 1, 2005•30 citations

A Probabilistic Algorithm for Computing the Weight Distribution of LDPC Codes

Masanori Hirotomo, Masami Mohri, Masakatu Morii

Low-density parity-check (LDPC) codes are linear block codes defined by sparse parity-check matrices. The codes exhibit excellent performance under iterative decoding, and the weight distribution is used to analyze lower error probability of their decoding performance. In this paper, we propose a probabilistic method for computing the weight distribution of LDPC codes. The proposed method efficiently finds low-weight codewords in a given LDPC code by using Stern's algorithm, and stochastically computes the low part of the weight distribution from the frequency of the found codewords. It is based on a relation between the number of codewords with a given weight and the rate of generating the codewords in Stern's algorithm. In the numerical results for LDPC codes of length 504, 1008 and 4896, we could compute the weight distribution by the proposed method with greater accuracy than by conventional methods.

IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences•Jan 1, 2009•6 citations

An improvement on the modified weighted bit flipping decoding algorithm for LDPC codes

Ming Yan Jiang, Chunming Zhao, Zhihua Shi +1 more

We present a major improvement to the modified weighted bit flipping (MWBF) decoding algorithm for low density parity-check (LDPC) codes. We improve the flipping criterion by introducing a more efficient method for computing the reliability of the parity checks. We derive an approximate theoretical expression for the weighting factor and demonstrate its consistency with simulation results. The improved MWBF algorithm achieves a noticeable gain over the MWBF algorithm with only a modest increase in computational complexity.

IEEE Communications Letters•Sep 1, 2005•153 citations

A Modification to Weighted Bit-Flipping Decoding Algorithm for LDPC Codes Based on Reliability Adjustment

D. Qian, M. Jiang, Chihang Zhao +1 more

In this paper, a modification to the weighted bit- flipping (WBF) decoding algorithm for low-density parity-check (LDPC) codes is proposed. This modification, based on the adjustment in reliabilities of the check sums during iterative decoding, can be applied to various WBF algorithms. Our studies show that the modification can be achieved with a small increase in complexity, but leads to an appealing improvement in error performance.

International Conference on Communications•Jan 1, 2008•4 citations

Weighted Hard-Reliability Decoding Method for Non-binary LDPC Codes

Tao Gao, Xiurong Ma, Mingxin Liu

In this paper, we propose a weighted hard-reliability based one step majority-logic decoding algorithm for NON-Binary Low-Density Parity-Check (NB-LDPC) codes. To improve the information reliable of check nodes and the use efficiency of receive message, a weight reliability message method is proposed where only the weight values generated in the decoding initialization are reserved for the iterate decoding process. We also propose a new message reliability updating rule for each iterate decoding, in which only the unreliable variable nodes are updated. Simulation results show that our proposed weighted iterative hard-reliability (WIHRB) algorithm significantly improves the error-floor performance compared to the conventional truncate iterative hard-reliability (TIHRB) algorithms.

International Conference on Systems and Informatics (ICSAI)•Nov 1, 2018•0 citations
In the analysis of maximum-likelihood decoding performance of low-density parity-check (LDPC) codes, the weight distribution is an important factor. We presented a probabilistic method for computing the weight distribution of LDPC codes, and showed results of computing the weight distribution of several LDPC codes. In this paper, we improve our previously presented method and propose a probabilistic computation method with reliability for the weight distribution of LDPC codes. Using the proposed method, we can determine the weight distribution with small failure probability.
In the analysis of maximum-likelihood decoding performance of low-density parity-check (LDPC) codes, the weight distribution is an important factor. Some methods based on the error impluse method have presented in order to estimate the weight distribution of LDPC codes. However, these methods have no scheme which determine the number of codeword in LDPC codes. In this paper, we propose a reliability-based computation method for the weight distribution of LDPC codes using the probabilistic algorithm. Using the proposed method, we can determine the weight distribution of LDPC codes with small failure probability.
Low-density parity-check (LDPC) codes achieve outstanding performance by the sum-product decoder. Its performance approaches the maximum-likelihood (ML) decoding performance at high SNR region. Upper bounds on the error probability of the ML decoded LDPC codes can be computed using the weight distribution. Recently, X.-Y. Hu et al. presented an approximate algorithm for estimating the weight distribution of LDPC codes. However, the weight distribution computed by their method depends on the iterative decoding algorithm, and is not always estimated exactly. In this paper, we propose a probabilistic method for computing the low-part weight distribution of LDPC codes. Using our method, the approximate weight distribution of LDPC codes can be computed with high accuracy
Low-density parity-check (LDPC) codes are linear block codes defined by sparse parity-check matrices. The codes exhibit excellent performance under iterative decoding, and the weight distribution is used to analyze lower error probability of their decoding performance. In this paper, we propose a probabilistic method for computing the weight distribution of LDPC codes. The proposed method efficiently finds low-weight codewords in a given LDPC code by using Stern's algorithm, and stochastically computes the low part of the weight distribution from the frequency of the found codewords. It is based on a relation between the number of codewords with a given weight and the rate of generating the codewords in Stern's algorithm. In the numerical results for LDPC codes of length 504, 1008 and 4896, we could compute the weight distribution by the proposed method with greater accuracy than by conventional methods.
We present a major improvement to the modified weighted bit flipping (MWBF) decoding algorithm for low density parity-check (LDPC) codes. We improve the flipping criterion by introducing a more efficient method for computing the reliability of the parity checks. We derive an approximate theoretical expression for the weighting factor and demonstrate its consistency with simulation results. The improved MWBF algorithm achieves a noticeable gain over the MWBF algorithm with only a modest increase in computational complexity.
In this paper, we propose a weighted hard-reliability based one step majority-logic decoding algorithm for NON-Binary Low-Density Parity-Check (NB-LDPC) codes. To improve the information reliable of check nodes and the use efficiency of receive message, a weight reliability message method is proposed where only the weight values generated in the decoding initialization are reserved for the iterate decoding process. We also propose a new message reliability updating rule for each iterate decoding, in which only the unreliable variable nodes are updated. Simulation results show that our proposed weighted iterative hard-reliability (WIHRB) algorithm significantly improves the error-floor performance compared to the conventional truncate iterative hard-reliability (TIHRB) algorithms.