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

Improved Layered Minimum Sum Decoding Algorithm Based on Overestimation

Liu Yu, Lin Bai, Yaohui Hao

Published Sep 23, 2022• 0 citations
Publisher

Abstract

Quasi-cyclic low-density parity-check (QC-LDPC) codes are linear block codes with performance close to the Shannon limit. The layered minimum sum (LMS) decoding algorithm speeds up the decoding convergence by layering the check matrix and updating the nodes according to the layers. However, the MS algorithm has the problem of over estimation and affects the decoding performance due to its simplified strategy of MS algorithm updating the message of check nodes. Therefore, this paper proposes a layered minimum sum decoding algorithm based on overestimation. By setting the correction threshold and updating the check nodes by the conditions, the decoding performance is improved. When the code length is 2048 and the bit error rate is , the proposed algorithm can improve the decoding convergence speed by about 25% and obtain a coding gain of about 0.1 dB.

DOI
10.1145/3573942.3573996

Related papers

A Second Minimum Approximation Method for Layered Min-Sum Decoding of QC-LDPC Codes

Zijian Qin, Yangcan Zhou, Zhongfeng Wang

Low-density parity-check (LDPC) codes have attracted tremendous attention for their excellent error-correction performance and inherent fitness for high-parallelism implementation. With great complexity reduction and friendly for hardware implementation, the min-sum (MS) decoding algorithm for LDPC codes gains widespread applications in practical. In the MS decoding algorithm, finding the first two minima among input variable-to-check messages is the most complex part. To further reduce the complexity of the MS decoding algorithm, an efficient single-minimum (single-min) based layered MS decoding for quasi-cyclic LDPC (QC-LDPC) codes is proposed in this paper. It is found that statistically the difference between the first minimum and second minimum increases as the decoding becomes more convergent. Accordingly, in the proposed single-min scheme, the second minimum is approximately derived based on the first minimum and an index indicating the convergence degree. Besides, some other metrics that are easily obtained are used to refine the second minimum. Simulation results show that the proposed method can significantly improve the error-correction performance and lower the average number of iterations, compared with the state-of-the-art single-min based MS decoding algorithms.

Information Communication Technologies Conference (ICTC)•May 17, 2023•1 citation

A Low Complexity Decoding Algorithm Design Based on Quasi-Cyclic LDPC Codes

Cai Honghao, Yingkun Yang, Yi Qu

Entering the 5G era, the hardware design of low-density parity-check (LDPC) codes under the new standard has increasingly higher requirements on throughput. According to the geometric characteristics of the check matrices of the quasi-cyclicQC) LDCP codes under the CCSDS standard, this paper designs a layered dynamic normalized minimum sum algorithm(LDNMSA) under the pre-termination decoding based on de-layering scheme. The check matrix structure of this code is easy for hardware design and the storage resource consumption is low. The approximate replacement of the minimum sum algorithm(MSA) reduces the computational complexity of the check node update process. The determination of correction factors and inter-layer deletion thresholds through computer simulation improves the decoding performance and the speed of a single iteration, and adopt the layered scheduling scheme with optimized update order reduces the number of iterations required for decoding. Experimental results show that when the bit error rate(BER) is 10-5, the designed algorithm has a gain of approximately 0.5 dB compared to the MSA. The speed and calculation amounts to a single iteration are much lower than the log-likelihood-ratio(LLR) belief propagation(BP) algorithm and the performance is only less than 0.1dB.

International Conference on Computing, Electronics & Communications Engineering (iCCECE)•Aug 17, 2020•2 citations

Low Complexity Decoding Algorithm of QC-LDPC Code

Fanglong Yi, Pengjun Wang

Through the research on the decoding algorithm of low-density parity-check (LDPC) code, a low complexity decoding algorithm suitable for quasi-cyclic LDPC (QC-LDPC) code is proposed in this paper. The algorithm adopts layered decoding (LD), and the sub-minimum is replaced by the sum of an optimal correction factor and the minimum during the process of the check nodes update. Therefore, it is not required to find the sub-minimum and the computational complexity reduces significantly. Matlab simulation results show that the decoding performance of this algorithm is very near to min-sum (MS) algorithm, and more superior than single min-sum (SMS) algorithm.

IEEE Asia-Pacific Services Computing Conference (APSCC)•Dec 1, 2010•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

Two Improved Algorithms for Layered QC-LDPC Decoding Algorithm

Xiao Zheng, Qingsheng Hu, Jun Feng

Low-Density Parity-Check code is a kind of near-optimal error correction code. In order to improve the performance of layered decoding algorithms, two algorithms are put forward in this paper. In the first algorithm, additional messages are employed for the messages updating operation of each layer by using another layered part, making it possible to accelerate the speed of convergence. In the second one, a correction operation for certain type of errors is performed to improve the decoding performance. Simulation results show that more decoding gain and accelerated convergence can be obtained compared with the conventional layered decoding algorithms.

Conference proceedings - Canadian Conference on Electrical and Computer Engineering•May 1, 2018•4 citations

An improved-performance decoding algorithm of LDPC codes for layered decoding

Jia Li, Gaigai Yang, Zhiqiang Zhao

In order to reduce the bit error rate of low-density parity-check codes for layered decoding algorithm and improve the decoding convergence speed, an improved layered decoding algorithm is proposed. In layered decoding algorithm, updated bit nodes information can be used by check nodes in the iteration process while in dynamic decoding algorithm check nodes update in order according to the reliability. The proposed algorithm combines advantages of the layered and dynamic decoding algorithm. Moreover, compared with the definition of remaining information for check nodes in the dynamic decoding algorithm, a new method to evaluate the reliability is defined in the proposed algorithm. Based on 1/2 code rate china mobile multimedia broadcasting standard, simulation and comparison between the conventional layered decoding algorithm and the proposed layered decoding algorithm have been carried out. The simulation results show that under the same bit error rate, the signal to noise ratio of the improved algorithm reduces nearly 0.4dB as well as convergence speed improves obviously. The proposed layered decoding algorithm reduces the bit error rate and improves the reliability of data in communication system which uses LDPC codes as the channel coding.

IEEE International Conference on Communication Problem-Solving•Dec 1, 2014•1 citation
Quasi-cyclic low-density parity-check (QC-LDPC) codes are linear block codes with performance close to the Shannon limit. The layered minimum sum (LMS) decoding algorithm speeds up the decoding convergence by layering the check matrix and updating the nodes according to the layers. However, the MS algorithm has the problem of over estimation and affects the decoding performance due to its simplified strategy of MS algorithm updating the message of check nodes. Therefore, this paper proposes a layered minimum sum decoding algorithm based on overestimation. By setting the correction threshold and updating the check nodes by the conditions, the decoding performance is improved. When the code length is 2048 and the bit error rate is , the proposed algorithm can improve the decoding convergence speed by about 25% and obtain a coding gain of about 0.1 dB.
Low-density parity-check (LDPC) codes have attracted tremendous attention for their excellent error-correction performance and inherent fitness for high-parallelism implementation. With great complexity reduction and friendly for hardware implementation, the min-sum (MS) decoding algorithm for LDPC codes gains widespread applications in practical. In the MS decoding algorithm, finding the first two minima among input variable-to-check messages is the most complex part. To further reduce the complexity of the MS decoding algorithm, an efficient single-minimum (single-min) based layered MS decoding for quasi-cyclic LDPC (QC-LDPC) codes is proposed in this paper. It is found that statistically the difference between the first minimum and second minimum increases as the decoding becomes more convergent. Accordingly, in the proposed single-min scheme, the second minimum is approximately derived based on the first minimum and an index indicating the convergence degree. Besides, some other metrics that are easily obtained are used to refine the second minimum. Simulation results show that the proposed method can significantly improve the error-correction performance and lower the average number of iterations, compared with the state-of-the-art single-min based MS decoding algorithms.
Entering the 5G era, the hardware design of low-density parity-check (LDPC) codes under the new standard has increasingly higher requirements on throughput. According to the geometric characteristics of the check matrices of the quasi-cyclicQC) LDCP codes under the CCSDS standard, this paper designs a layered dynamic normalized minimum sum algorithm(LDNMSA) under the pre-termination decoding based on de-layering scheme. The check matrix structure of this code is easy for hardware design and the storage resource consumption is low. The approximate replacement of the minimum sum algorithm(MSA) reduces the computational complexity of the check node update process. The determination of correction factors and inter-layer deletion thresholds through computer simulation improves the decoding performance and the speed of a single iteration, and adopt the layered scheduling scheme with optimized update order reduces the number of iterations required for decoding. Experimental results show that when the bit error rate(BER) is 10-5, the designed algorithm has a gain of approximately 0.5 dB compared to the MSA. The speed and calculation amounts to a single iteration are much lower than the log-likelihood-ratio(LLR) belief propagation(BP) algorithm and the performance is only less than 0.1dB.
Through the research on the decoding algorithm of low-density parity-check (LDPC) code, a low complexity decoding algorithm suitable for quasi-cyclic LDPC (QC-LDPC) code is proposed in this paper. The algorithm adopts layered decoding (LD), and the sub-minimum is replaced by the sum of an optimal correction factor and the minimum during the process of the check nodes update. Therefore, it is not required to find the sub-minimum and the computational complexity reduces significantly. Matlab simulation results show that the decoding performance of this algorithm is very near to min-sum (MS) algorithm, and more superior than single min-sum (SMS) algorithm.
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 code is a kind of near-optimal error correction code. In order to improve the performance of layered decoding algorithms, two algorithms are put forward in this paper. In the first algorithm, additional messages are employed for the messages updating operation of each layer by using another layered part, making it possible to accelerate the speed of convergence. In the second one, a correction operation for certain type of errors is performed to improve the decoding performance. Simulation results show that more decoding gain and accelerated convergence can be obtained compared with the conventional layered decoding algorithms.
In order to reduce the bit error rate of low-density parity-check codes for layered decoding algorithm and improve the decoding convergence speed, an improved layered decoding algorithm is proposed. In layered decoding algorithm, updated bit nodes information can be used by check nodes in the iteration process while in dynamic decoding algorithm check nodes update in order according to the reliability. The proposed algorithm combines advantages of the layered and dynamic decoding algorithm. Moreover, compared with the definition of remaining information for check nodes in the dynamic decoding algorithm, a new method to evaluate the reliability is defined in the proposed algorithm. Based on 1/2 code rate china mobile multimedia broadcasting standard, simulation and comparison between the conventional layered decoding algorithm and the proposed layered decoding algorithm have been carried out. The simulation results show that under the same bit error rate, the signal to noise ratio of the improved algorithm reduces nearly 0.4dB as well as convergence speed improves obviously. The proposed layered decoding algorithm reduces the bit error rate and improves the reliability of data in communication system which uses LDPC codes as the channel coding.