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

arXiv:1207.5555 · IEEE Transactions on Communications

A Simplified Min-Sum Decoding Algorithm for Non-Binary LDPC Codes

Chung-Li Wang, Xiaoheng Chen, Zongwang Li, Shaohua Yang

Published Oct 22, 2012• 50 citations
arXivHTMLPDF

Abstract

Non-binary low-density parity-check codes are robust to various channel impairments. However, based on the existing decoding algorithms, the decoder implementations are expensive because of their excessive computational complexity and memory usage. Based on the combinatorial optimization, we present an approximation method for the check node processing. The simulation results demonstrate that our scheme has small performance loss over the additive white Gaussian noise channel and independent Rayleigh fading channel. Furthermore, the proposed reduced-complexity realization provides significant savings on hardware, so it yields a good performance-complexity tradeoff and can be efficiently implemented.

DOI
10.1109/tcomm.2012.101712.110709

Related papers

A new min-sum based decoding algorithm for non-binary LDPC codes

Chung-Li Wang, Zongwang Li, Shaohua Yang

Non-binary low-density parity-check (NB-LDPC) codes are robust to various channel impairments. In this paper, we present a new decoding algorithm for the NB-LDPC decoder that is based on the q-ary min-sum algorithm (QMSA). The new one modifies the check node (CN) computations of the QMSA into two steps. By reorganizing the message entries and providing the most likely symbol, a compressed intermediate message can be easily obtained and stored, from which the check-to-variable messages can be computed with a look-up table. Thus the decoder architecture can have a straightforward design for the CN with reduced complexity and memory requirements. Besides, the simulation results demonstrate that the proposed algorithm has negligible performance loss compared to the QMSA over AWGN channel.

2012 International Conference on Computing, Networking and Communications (ICNC)•Jan 1, 2012•5 citations

Optimized Min-Sum Decoding Algorithm for Low Density Parity Check Codes

Mohammad Rakibul, Dewan Siam Shafiullah, Muhammad Mostafa +1 more

Low Density Parity Check (LDPC) code approaches Shannon–limit performance for binary field and long code lengths. However, performance of binary LDPC code is degraded when the code word length is small. An optimized min-sum algorithm for LDPC code is proposed in this paper. In this algorithm unlike other decoding methods, an optimization factor has been introduced in both check node and bit node of the Min-sum algorithm. The optimization factor is obtained before decoding program, and the same factor is multiplied twice in one cycle. So the increased complexity is fairly low. Simulation results show that the proposed Optimized Min-Sum decoding algorithm performs very close to the Sum-Product decoding while preserving the main features of the Min-Sum decoding, that is low complexity and independence with respect to noise variance estimation errors.

International Journal of Advanced Computer Science and Applications•Jan 1, 2011•19 citations

Optimized Min-Sum Decoding Algorithm for Low Density Parity Check Codes

Mohammad Rakibul Islam, Dewan Siam Shafiullah, Muhammad Mostafa +2 more

Abstract ― Low Density Parity Check (LDPC) code approaches Shannon–limit performance for binary field and long code lengths. However, performance of binary LDPC code is degraded when the code word length is small. An optimized min-sum algorithm for LDPC code is proposed in this paper. In this algorithm unlike other decoding methods, an optimization factor has been introduced in both check node and bit node of the Min-sum algorithm. The optimization factor is obtained before decoding program, and the same factor is multiplied twice in one cycle. So the increased complexity is fairly low. Simulation results show that the proposed Optimized Min-Sum decoding algorithm performs very close to the Sum-Product decoding while preserving the main features of the Min-Sum decoding, that is low complexity and independence with respect to noise variance estimation errors.

•Oct 31, 2015•2 citations

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

Set min-sum decoding algorithm for non-binary LDPC codes

Liyuan Song, Qin Huang, Zulin Wang

This paper reduces the complexity of decoding non-binary low-density parity-check (LDPC) codes by set partition. In the check node update, the input vectors are partitioned into several sets such that different elements in the virtual matrix enjoy various computational strategies. As a result, the proposed algorithm achieves high computational efficiency by setting strategies according to the correct probability of these elements. Simulation results indicate that it significantly decreases the complexity of check node update with negligible performance loss.

IEEE International Symposium on Information Theory (ISIT)•Jul 1, 2016•9 citations

Hardware efficient decoding of LDPC codes using partial-min algorithms

Jiabin Su, K. Liu, Hao Min

In this paper, the partial-min algorithms are proposed for updating the check node messages in decoding low-density parity-check (LDPC) codes. The proposed methods can achieve a good performance-versus-complexity tradeoff by reducing both the check node processor complexity and the decoder memory requirements. Float-point and fixed-point simulation results show that a near optimum performance can be maintained. The architecture of a check node processor implementing the partial-min algorithms is also presented. The hardware expense especially the memory requirement is analyzed and compared with normal decoding architectures

IEEE Transactions on Consumer Electronics•Nov 1, 2006•6 citations
Non-binary low-density parity-check codes are robust to various channel impairments. However, based on the existing decoding algorithms, the decoder implementations are expensive because of their excessive computational complexity and memory usage. Based on the combinatorial optimization, we present an approximation method for the check node processing. The simulation results demonstrate that our scheme has small performance loss over the additive white Gaussian noise channel and independent Rayleigh fading channel. Furthermore, the proposed reduced-complexity realization provides significant savings on hardware, so it yields a good performance-complexity tradeoff and can be efficiently implemented.
Non-binary low-density parity-check (NB-LDPC) codes are robust to various channel impairments. In this paper, we present a new decoding algorithm for the NB-LDPC decoder that is based on the q-ary min-sum algorithm (QMSA). The new one modifies the check node (CN) computations of the QMSA into two steps. By reorganizing the message entries and providing the most likely symbol, a compressed intermediate message can be easily obtained and stored, from which the check-to-variable messages can be computed with a look-up table. Thus the decoder architecture can have a straightforward design for the CN with reduced complexity and memory requirements. Besides, the simulation results demonstrate that the proposed algorithm has negligible performance loss compared to the QMSA over AWGN channel.
Low Density Parity Check (LDPC) code approaches Shannon–limit performance for binary field and long code lengths. However, performance of binary LDPC code is degraded when the code word length is small. An optimized min-sum algorithm for LDPC code is proposed in this paper. In this algorithm unlike other decoding methods, an optimization factor has been introduced in both check node and bit node of the Min-sum algorithm. The optimization factor is obtained before decoding program, and the same factor is multiplied twice in one cycle. So the increased complexity is fairly low. Simulation results show that the proposed Optimized Min-Sum decoding algorithm performs very close to the Sum-Product decoding while preserving the main features of the Min-Sum decoding, that is low complexity and independence with respect to noise variance estimation errors.
Abstract ― Low Density Parity Check (LDPC) code approaches Shannon–limit performance for binary field and long code lengths. However, performance of binary LDPC code is degraded when the code word length is small. An optimized min-sum algorithm for LDPC code is proposed in this paper. In this algorithm unlike other decoding methods, an optimization factor has been introduced in both check node and bit node of the Min-sum algorithm. The optimization factor is obtained before decoding program, and the same factor is multiplied twice in one cycle. So the increased complexity is fairly low. Simulation results show that the proposed Optimized Min-Sum decoding algorithm performs very close to the Sum-Product decoding while preserving the main features of the Min-Sum decoding, that is low complexity and independence with respect to noise variance estimation errors.
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.
This paper reduces the complexity of decoding non-binary low-density parity-check (LDPC) codes by set partition. In the check node update, the input vectors are partitioned into several sets such that different elements in the virtual matrix enjoy various computational strategies. As a result, the proposed algorithm achieves high computational efficiency by setting strategies according to the correct probability of these elements. Simulation results indicate that it significantly decreases the complexity of check node update with negligible performance loss.
In this paper, the partial-min algorithms are proposed for updating the check node messages in decoding low-density parity-check (LDPC) codes. The proposed methods can achieve a good performance-versus-complexity tradeoff by reducing both the check node processor complexity and the decoder memory requirements. Float-point and fixed-point simulation results show that a near optimum performance can be maintained. The architecture of a check node processor implementing the partial-min algorithms is also presented. The hardware expense especially the memory requirement is analyzed and compared with normal decoding architectures