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

International Conference on Sensors and Information Technology (ICSI)

A Self-Correcting Minimum Sum Algorithm with Dual Reliability

Zhaochuan Wei, Xiaoqian Zhou, Yuanfa Ji, Somsack Inthaseone

Published Mar 21, 2025• 0 citations
Publisher

Abstract

In order to improve the performance and reliability of Low-Density Parity-Check (LDPC) code decoding algorithms, this paper proposes a Self-Correcting Minimum Sum algorithm with Dual Reliability Determination (DRD-SCMS) to address the limitations of the Self-Correcting Minimum Sum (SCMS) algorithm in determining the reliability of variable nodes. Unlike the traditional SCMS algorithm, which relies solely on the symbols from the previous and current iterations to assess the reliability of variable nodes, the DRD-SCMS algorithm combines the number of connections between variable nodes and check nodes with check failures, along with the results of symbol iterations, to provide a more accurate reliability evaluation. By categorizing variable nodes into three groups and prioritizing the updating of the most unreliable nodes, the algorithm optimizes the iteration order in the decoding process. Simulation results demonstrate that the DRD-SCMS algorithm significantly reduces the number of iterations and improves decoding efficiency compared to the SCMS algorithm, offering better applicability and reliability.

DOI
10.1109/icsi64877.2025.11009386

Related papers

Dual Threshold Self-Corrected Minimum Sum Algorithm for 5G LDPC Decoders

Rong Chen, Lan Chen

Fifth generation (5G) is a new generation mobile communication system developed for the growing demand for mobile communication. Channel coding is an indispensable part of most modern digital communication systems, for it can improve the transmission reliability and anti-interference. In order to meet the requirements of 5G communication, a dual threshold self-corrected minimum sum (DT-SCMS) algorithm for low-density parity-check (LDPC) decoders is proposed in this paper. Besides, an architecture of LDPC decoders is designed. By setting thresholds to judge the reliability of messages, the DT-SCMS algorithm erases unreliable messages, improving the decoding performance and efficiency. Simulation results show that the performance of DT-SCMS is better than that of SCMS. When the code rate is 1/3, the performance of DT-SCMS has been improved by 0.2 dB at the bit error rate of 10 − 4 compared with SCMS. In terms of the convergence, when the code rate is 2/3, the number of iterations of DT-SCMS can be reduced by up to 20.46% compared with SCMS, and the average proportion of reduction is 18.68%.

Information•Jul 7, 2020•3 citations

An Improved Self-Corrected Min-Sum Decoding for LDPC Codes

Xingjin Li, Liguo Zhang, Jingxuan Tan +3 more

Low-Density Parity-Check (LDPC) code is a linear block code approaching the Shannon limit. The improvement of the decoding performance of LDPC codes is a hot research direction today. To improve the decoding performance of the self-correcting min-sum (SCMS) algorithm, an improved self-correcting min-sum (ISCMS) algorithm is proposed based on this algorithm. In the iterative decoding process of the ISCMS algorithm, the update rule of the check node (CN) is optimized to the update rule of the CN of the IOMS algorithm, which improves the accuracy of decoding from the processing of the CN. Simulation results show that the proposed ISCMS algorithm has better error performance and convergence performance than the SCMS algorithm with a small increase in computational complexity.

International Conference on Intelligent Systems and Knowledge Engineering (ISKE)•Nov 26, 2021•0 citations

Improved Extended Min-Sum Algorithm for Non-Binary LDPC Codes Based on Node Reliability

Yibing Li, Sitong Zhang, Fang Ye +3 more

Low Density Parity Check (LDPC) codes have been widely applied in recent years, and Extended Min-Sum (EMS) decoding algorithm is the most practical algorithm, which has a fairly low computational cost. Due to the great loss in error correction performance of EMS algorithm, in this paper, we establish constraints to obtain reliable nodes while decoding and evaluate the reliability of the nodes. The nodes and information transferred between nodes are processed and optimized according to the reliability of the nodes. High reliability nodes will not be updated in the decoding process while the information of the sub-reliability nodes will be optimized in different situations, thereby improving the decoding accuracy. This algorithm can accelerate the convergence of the algorithm, while the reduced number of update nodes can control the increase of the computation to a certain extent, and maintain the advantage of the low computation quantity of EMS algorithm. Through simulation results and computational analysis, we prove that the improved algorithm has significantly improved error correction performance compared with the traditional EMS algorithm. Under the same conditions, it has completely entered the waterfall area at 3.6dB, and the EMS algorithm has not entered the waterfall area. By comparing the average iteration times of decoding of the two algorithms, the convergence speed of the algorithm can be reflected. Compared with EMS algorithm, the improved algorithm has significantly improved the convergence speed in most areas, which indicates that the processing of sub-reliable nodes accelerates the convergence of the algorithm. Finally, the average update times of the check nodes and variable nodes of the two algorithms are compared respectively. Although the improved algorithm introduces extra processing flow, it speeds up the convergence of the algorithm, and the computational cost of decoding is less expensive.

IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications (APWC)•Sep 1, 2019•0 citations

Improved Min-sum Algorithm with Low Complexity for Decoding LDPC Codes

Wu Ju

In order to reduce the performance loss of SMMS( Single-Minimum,Min-Sum) algorithm for decoding LDPC( LowDensity Parity-Check) codes,the ACMS( adaptive configurable Min-Sum) algorithm is proposed in this paper. Only the absolute minimum is used in this algorithm to update the check-node message and the second minimum is determined by a configurable estimation weight factor based on the iteration and a correction factor based on the number of error bits in each hard decision. Compared to the original SMMS and VWMS algorithm,the simulation result shows the proposed ACMS algorithm reduce the performance loss in general by introducing only a little additional complexity.

Video Engineering•Jan 1, 2015•0 citations

A Multi-parameter Compensated Min-Sum Based LDPC Decoding Algorithm

Shuxun He, Cheng Wang, Songsong Cai +1 more

The Minimum Sum (MS) algorithm is a standard Low-Density Parity-Check Codes (LDPC) decoding algorithm. Compared with traditional algorithms, it uses approximate calculations to reduce the computational complexity of the algorithm when calculating parity nodes, resulting in performance loss issues. To improve the LDPC decoding performance, the LDPC decoding algorithm of Multi-parameter Compensated Min-Sum (MCMS) is proposed. This algorithm introduces relevant information, such as channel and code length, into calculating update verification nodes. Introducing multiplication and correction factors to reduce errors in validation node calculations through multi-parameter compensation. Simulation results show that the MCMS algorithm has superior error rate performance compared with the MS algorithm.

IEEE International Conference on Computer and Communications (ICCC)•Dec 8, 2023•1 citation

Improved layered min-sum decoding algorithm for low density parity check codes

Jin Xie, Liuguo Yin, Ning Ge +1 more

In this paper, an improved layered min-sum (ILMS) algorithm is proposed for the decoding of low-density parity-check (LDPC) codes. The proposed method speeds up the decoding by slightly amplifying the message update from check node to variable node. Simulations and analytical results show that compared with the standard layered min-sum decoding algorithm, the proposed scheme may reduce the number of iterations by 8.4%-62.6%, with hardware increase less than 2%.

•May 20, 2009•1 citation
In order to improve the performance and reliability of Low-Density Parity-Check (LDPC) code decoding algorithms, this paper proposes a Self-Correcting Minimum Sum algorithm with Dual Reliability Determination (DRD-SCMS) to address the limitations of the Self-Correcting Minimum Sum (SCMS) algorithm in determining the reliability of variable nodes. Unlike the traditional SCMS algorithm, which relies solely on the symbols from the previous and current iterations to assess the reliability of variable nodes, the DRD-SCMS algorithm combines the number of connections between variable nodes and check nodes with check failures, along with the results of symbol iterations, to provide a more accurate reliability evaluation. By categorizing variable nodes into three groups and prioritizing the updating of the most unreliable nodes, the algorithm optimizes the iteration order in the decoding process. Simulation results demonstrate that the DRD-SCMS algorithm significantly reduces the number of iterations and improves decoding efficiency compared to the SCMS algorithm, offering better applicability and reliability.
Fifth generation (5G) is a new generation mobile communication system developed for the growing demand for mobile communication. Channel coding is an indispensable part of most modern digital communication systems, for it can improve the transmission reliability and anti-interference. In order to meet the requirements of 5G communication, a dual threshold self-corrected minimum sum (DT-SCMS) algorithm for low-density parity-check (LDPC) decoders is proposed in this paper. Besides, an architecture of LDPC decoders is designed. By setting thresholds to judge the reliability of messages, the DT-SCMS algorithm erases unreliable messages, improving the decoding performance and efficiency. Simulation results show that the performance of DT-SCMS is better than that of SCMS. When the code rate is 1/3, the performance of DT-SCMS has been improved by 0.2 dB at the bit error rate of 10 − 4 compared with SCMS. In terms of the convergence, when the code rate is 2/3, the number of iterations of DT-SCMS can be reduced by up to 20.46% compared with SCMS, and the average proportion of reduction is 18.68%.
Low-Density Parity-Check (LDPC) code is a linear block code approaching the Shannon limit. The improvement of the decoding performance of LDPC codes is a hot research direction today. To improve the decoding performance of the self-correcting min-sum (SCMS) algorithm, an improved self-correcting min-sum (ISCMS) algorithm is proposed based on this algorithm. In the iterative decoding process of the ISCMS algorithm, the update rule of the check node (CN) is optimized to the update rule of the CN of the IOMS algorithm, which improves the accuracy of decoding from the processing of the CN. Simulation results show that the proposed ISCMS algorithm has better error performance and convergence performance than the SCMS algorithm with a small increase in computational complexity.
Low Density Parity Check (LDPC) codes have been widely applied in recent years, and Extended Min-Sum (EMS) decoding algorithm is the most practical algorithm, which has a fairly low computational cost. Due to the great loss in error correction performance of EMS algorithm, in this paper, we establish constraints to obtain reliable nodes while decoding and evaluate the reliability of the nodes. The nodes and information transferred between nodes are processed and optimized according to the reliability of the nodes. High reliability nodes will not be updated in the decoding process while the information of the sub-reliability nodes will be optimized in different situations, thereby improving the decoding accuracy. This algorithm can accelerate the convergence of the algorithm, while the reduced number of update nodes can control the increase of the computation to a certain extent, and maintain the advantage of the low computation quantity of EMS algorithm. Through simulation results and computational analysis, we prove that the improved algorithm has significantly improved error correction performance compared with the traditional EMS algorithm. Under the same conditions, it has completely entered the waterfall area at 3.6dB, and the EMS algorithm has not entered the waterfall area. By comparing the average iteration times of decoding of the two algorithms, the convergence speed of the algorithm can be reflected. Compared with EMS algorithm, the improved algorithm has significantly improved the convergence speed in most areas, which indicates that the processing of sub-reliable nodes accelerates the convergence of the algorithm. Finally, the average update times of the check nodes and variable nodes of the two algorithms are compared respectively. Although the improved algorithm introduces extra processing flow, it speeds up the convergence of the algorithm, and the computational cost of decoding is less expensive.
In order to reduce the performance loss of SMMS( Single-Minimum,Min-Sum) algorithm for decoding LDPC( LowDensity Parity-Check) codes,the ACMS( adaptive configurable Min-Sum) algorithm is proposed in this paper. Only the absolute minimum is used in this algorithm to update the check-node message and the second minimum is determined by a configurable estimation weight factor based on the iteration and a correction factor based on the number of error bits in each hard decision. Compared to the original SMMS and VWMS algorithm,the simulation result shows the proposed ACMS algorithm reduce the performance loss in general by introducing only a little additional complexity.
The Minimum Sum (MS) algorithm is a standard Low-Density Parity-Check Codes (LDPC) decoding algorithm. Compared with traditional algorithms, it uses approximate calculations to reduce the computational complexity of the algorithm when calculating parity nodes, resulting in performance loss issues. To improve the LDPC decoding performance, the LDPC decoding algorithm of Multi-parameter Compensated Min-Sum (MCMS) is proposed. This algorithm introduces relevant information, such as channel and code length, into calculating update verification nodes. Introducing multiplication and correction factors to reduce errors in validation node calculations through multi-parameter compensation. Simulation results show that the MCMS algorithm has superior error rate performance compared with the MS algorithm.