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

Jisuanji gongcheng

Efficient LDPC Decoding Algorithm Based on Min-sum

Jingao Liu

Published Jan 1, 2009• 0 citations
OpenAlex

Abstract

To improve the decoding performance of Low Density Parity Check(LDPC) code,an efficient decoding algorithm based on min-sum algorithm is proposed. The proposed algorithm analyzes the check node update equation and at the view of probability to form an approximation min-sum equation. It adopts a dynamic normalization factor to improve the decoding performance. Detailed simulation results and comparisons with Belief Propagation(BP) algorithm show that,with little decoding performance loss,the proposed algorithm not only decreases computational load,but also improves decoding efficiency.

Related papers

Differential Decoding of Low-Density Parity-Check Codes Based on Min Sum Algorithm

Shizhang Peng, Zemao Zhao, Jianrong Bao

To improve performance and reduce computation complexity of the low-density parity-check (LDPC) codes, a min-sum based differential decoding algorithm is proposed. The main principle is that the messages passing in the bipartite graph of the codes are the probability differences and the updates of the check nodes adopt min sum algorithm. Simulation results show that the proposed algorithm can achieve about 0.4dB performance gain over the UMP BP-Based decoding algorithm at bit error rate (BER) of under an additive white Gaussian noise (AWGN) channel. And it can obtain good performance very close to that of the BP decoding algorithm with much lower complexity.

International Symposium on Information Science and Engineering•Dec 1, 2010•2 citations

An improved normalized min-sum algorithm for LDPC codes

Jinlei Chen, Yan Zhang, Ruiyi Sun

An improved normalized min-sum (IN-MS) algorithm is proposed for decoding low-density parity-check (LDPC) codes. In this algorithm, two normalized factors are used in check node computing, one for the minimum data and another for the second minimum data, and this algorithm achieves a better approximation to the BP algorithm. Simulation results show that the decoding performance of IN-MS algorithm is better than that of the normalized min-sum (NMS) algorithm.

IEEE/ACIS International Conference on Computer and Information Science (ICIS)•Jun 1, 2013•9 citations

A Improved Min-Sum Algorithm for LDPC Codes

Zhang Rong-rong

Among the decoding algorithm for low-density parity-check(LDPC) code,belief propagation(BP) algorithm has good performance but high complexity,while min-sum algorithm has simple implementation complexity but worse performance.Considering the trade-off between performance and complexity,the relationship between the value of overestimate under min-sum algorithm and the input information is analyzed,and an improved min-sum algorithm is proposed.Simulation results show that the improved min-sum algorithm remains similar performance with the traditional BP algorithm,but has less complexity.

Microcomputer Information•Jan 1, 2010•0 citations

A modified Offset Min-Sum decoding algorithm for LDPC codes

Meng Xu, Jianhui Wu, Meng Zhang

In this paper a modified Offset Min-Sum decoding algorithm for Low-Density Parity Check Codes is presented. In this modified algorithm, the offset factor in the original Offset Min-Sum algorithm is adjusted iteratively with the assistance of the check-node computation outputs of the Normalized Min-Sum algorithm. As a result, the offset factor in our modified algorithm can be calculated adaptively and more efficiently according to the previous decoding procedure, which can minimize the decoding degradation compared with the Belief Propagation decoding algorithm. The simulation results show that, compared with the original Offset Min-Sum decoding algorithm, our modified algorithm can achieve noticeable performance improvement with minor extra hardware complexity. For example, when BER is 10−5, our algorithm can achieve 0.1dB and 0.2dB decoding gain over Offset Min-Sum algorithm for regular and irregular LDPC codes respectively.

•Jul 1, 2010•29 citations

A modified Min-Sum algorithm for low-density parity-check codes

Wei Han, Jianguo Huang, WU Fang-fei

A modified Min-Sum algorithm for low-density parity check codes is proposed in this paper. The inaccurate check node messages of the Min-Sum algorithm compared to the belief propagation (BP) algorithm are compensated by modified variable node messages, which is different from the normalized Min-Sum algorithm. The modified factor is obtained before decoding program and only one extra multiplication is needed in one cycle. So the increased complexity is fairly low. The simulation results show that the bit error rate (BER) and average number of iteration of the modified Min-Sum algorithm are very close to the BP algorithm, the modified algorithm can improve the BER performance compared to the Min-Sum algorithm while added complexity slightly.

Wireless Communications, Networking and Information Security•Jun 1, 2010•9 citations

Modified min-sum decoding algorithm for LDPC codes based on classified correction

Zhong Zhou, Yunzhou Li, Xiang Chen +2 more

In this paper, a modified min-sum decoding algorithm based on classified correction is proposed for low density parity check (LDPC) codes. Different from the single correction in the normalized belief propagation (BP)-based and offset BP-based algorithms [4], the proposed algorithm utilizes two corrections for both minimum and sub-minimum magnitudes of input messages in check nodes. These two correction factors can be obtained by analyzing the offset of updated messages in check nodes between the BP and the min-sum algorithms associated with check node degree. Simulation results show that the proposed algorithm can achieve performance very close to that of the BP algorithm. Furthermore, the FPGA implementation of this algorithm can reach a throughput of 200 Mbps at BER=10-6with lower complexity and fewer resources than the BP algorithm.

International Conference on Communications and Networking in China (ChinaCom)•Aug 1, 2008•9 citations
To improve the decoding performance of Low Density Parity Check(LDPC) code,an efficient decoding algorithm based on min-sum algorithm is proposed. The proposed algorithm analyzes the check node update equation and at the view of probability to form an approximation min-sum equation. It adopts a dynamic normalization factor to improve the decoding performance. Detailed simulation results and comparisons with Belief Propagation(BP) algorithm show that,with little decoding performance loss,the proposed algorithm not only decreases computational load,but also improves decoding efficiency.
To improve performance and reduce computation complexity of the low-density parity-check (LDPC) codes, a min-sum based differential decoding algorithm is proposed. The main principle is that the messages passing in the bipartite graph of the codes are the probability differences and the updates of the check nodes adopt min sum algorithm. Simulation results show that the proposed algorithm can achieve about 0.4dB performance gain over the UMP BP-Based decoding algorithm at bit error rate (BER) of under an additive white Gaussian noise (AWGN) channel. And it can obtain good performance very close to that of the BP decoding algorithm with much lower complexity.
Among the decoding algorithm for low-density parity-check(LDPC) code,belief propagation(BP) algorithm has good performance but high complexity,while min-sum algorithm has simple implementation complexity but worse performance.Considering the trade-off between performance and complexity,the relationship between the value of overestimate under min-sum algorithm and the input information is analyzed,and an improved min-sum algorithm is proposed.Simulation results show that the improved min-sum algorithm remains similar performance with the traditional BP algorithm,but has less complexity.
In this paper a modified Offset Min-Sum decoding algorithm for Low-Density Parity Check Codes is presented. In this modified algorithm, the offset factor in the original Offset Min-Sum algorithm is adjusted iteratively with the assistance of the check-node computation outputs of the Normalized Min-Sum algorithm. As a result, the offset factor in our modified algorithm can be calculated adaptively and more efficiently according to the previous decoding procedure, which can minimize the decoding degradation compared with the Belief Propagation decoding algorithm. The simulation results show that, compared with the original Offset Min-Sum decoding algorithm, our modified algorithm can achieve noticeable performance improvement with minor extra hardware complexity. For example, when BER is 10−5, our algorithm can achieve 0.1dB and 0.2dB decoding gain over Offset Min-Sum algorithm for regular and irregular LDPC codes respectively.
A modified Min-Sum algorithm for low-density parity check codes is proposed in this paper. The inaccurate check node messages of the Min-Sum algorithm compared to the belief propagation (BP) algorithm are compensated by modified variable node messages, which is different from the normalized Min-Sum algorithm. The modified factor is obtained before decoding program and only one extra multiplication is needed in one cycle. So the increased complexity is fairly low. The simulation results show that the bit error rate (BER) and average number of iteration of the modified Min-Sum algorithm are very close to the BP algorithm, the modified algorithm can improve the BER performance compared to the Min-Sum algorithm while added complexity slightly.
In this paper, a modified min-sum decoding algorithm based on classified correction is proposed for low density parity check (LDPC) codes. Different from the single correction in the normalized belief propagation (BP)-based and offset BP-based algorithms [4], the proposed algorithm utilizes two corrections for both minimum and sub-minimum magnitudes of input messages in check nodes. These two correction factors can be obtained by analyzing the offset of updated messages in check nodes between the BP and the min-sum algorithms associated with check node degree. Simulation results show that the proposed algorithm can achieve performance very close to that of the BP algorithm. Furthermore, the FPGA implementation of this algorithm can reach a throughput of 200 Mbps at BER=10-6with lower complexity and fewer resources than the BP algorithm.