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 Wireless Communications, Networking and Mobile Computing

Two Efficient Algorithms Based on Majority-Logic and Min-Sum Algorithms for LDPC Codes

Zuotao Zhang, Yibo Fang, Guanghui Liu

Published Sep 1, 2012• 0 citations
Publisher

Abstract

Recently, an iterative soft information reliability-based majority-logic (ISRB-MLG) decoding algorithm was proposed for Euclidean geometry LDPC (EG-LDPC) and Projective geometry LDPC (PG-LDPC) codes. This paper first presents an iterative soft information reliability-based min-sum (ISRB-MS) decoding algorithm based on ISRB-MLG and traditional min-sum decoding algorithm. The performance of ISRB-MS algorithm is greatly improved with a little more complexity than ISRB-MLG algorithm, it mainly needs integer additions and logical operations. Different from traditional min-sum decoding algorithm, the extrinsic information transfer of ISRB-MS algorithm is simplified, we use the full information that all check nodes pass rather than the extrinsic information to update the bit nodes information. Then a modified iterative soft information reliability-based min-sum (MISRB-MS) decoding algorithm is proposed. Compared to (ISRB-MS) algorithm, MISRB-MS algorithm multiplies a scaling factor, so it needs some extra multiplication, but it achieves better performance. Simulation results show that the two algorithms achieve excellent performance and fast convergence rate, they only needs about 10 iterations, if an appropriate scaling factor is chosen, the performance of MISRB-MS algorithm very closes to that of sum-product algorithm (SPA).

DOI
10.1109/wicom.2012.6478732

Related papers

Improved iterative soft-reliability-based majority-logic decoding algorithm for non-binary low-density parity-check codes

Chenrong Xiong, Zhiyuan Yan

Non-binary low-density parity-check (LDPC) codes have some advantages as opposed to their binary counterparts, but unfortunately their decoding complexity is a significant challenge. Hence, the iterative soft-reliability-based (ISRB) majority-logic decoding algorithm is attractive for non-binary LDPC codes, since it involves only finite field additions and multiplications as well as integer additions and comparisons. In this paper, we propose an improved ISRB majority-logic decoding algorithm by using a new reliability update. Our improved algorithm achieves better error performance and faster convergence, while further reducing the computational complexity. For instance, for a (16, 16)-regular (255, 175) cyclic Euclidean geometry LDPC code over GF(28), the proposed algorithm achieves a 0.15 dB coding gain and improves the convergence speed by 10% at a block error rate of 10-4versus the ISRB majority-logic decoding algorithm. Compared with the ISRB majority-logic decoding algorithm, the proposed algorithm requires the same numbers of finite field additions and multiplications but fewer integer additions and comparisons. Furthermore, the ISRB majority-logic decoding algorithm is based on the accumulation of reliability information, and hence the numerical range of the reliability information increases with iterations. In contrast, the proposed reliability update has a fixed numerical range and thus simplifies hardware implementations.

Asilomar Conference on Signals, Systems and Computers (ACSSC)•Nov 1, 2011•23 citations

Comparisons Between Reliability-Based Iterative Min-Sum and Majority-Logic Decoding Algorithms for LDPC Codes

Haiqiang Chen, Kai Zhang, Xiao Ma +1 more

A modified reliability-based iterative majority-logic decoding (MRBI-MLGD) algorithm for two classes of structured LDPC codes is presented based on a recent work by Huang et al. Compared with the original one, the modified algorithm has better performance with slightly increased complexity. Then a reliability-based iterative min-sum decoding (RBI-MSD) algorithm is presented. For the presented RBI-MSD algorithm, reliability-based integer messages are processed and exchanged between variable nodes and check nodes. The main computations include only binary logical operations and integer additions. Different from the conventional min-sum algorithm, the variable nodes pass full messages rather than extrinsic messages to check nodes. This can reduce the memory loads and the computational complexity but with a little (or negligible) performance degradation. Simulation results show that, compared with the (M)RBI-MLGD algorithms, the presented RBI-MSD algorithm achieves better error performance, faster decoding convergence rate and fewer quantization bits with moderate increased computational complexity. Furthermore, the RBI-MSD algorithm is also applicable to decoding random LDPC codes, a distinct difference from the (M)RBI-MLGD algorithms. Finally, we point out that the scaling factors employed in the MRBI-MLGD algorithm and the RBI-MSD algorithm can be optimized using discretized density evolution.

IEEE Transactions on Communications•Jun 28, 2011•23 citations

An efficient architecture for iterative soft reliability-based majority-logic non-binary LDPC decoding

Xinmiao Zhang, Fang Cai

Non-binary low-density parity-check (NB-LDPC) codes have better error-correcting performance than their binary counterparts at the cost of higher decoding complexity when the code length is moderate. Compared to other NB-LDPC decoding algorithms, the iterative reliability-based majority-logic decoding can achieve better performance-complexity tradeoff. In this paper, an efficient partial-parallel shift-message decoder architecture is proposed for cyclic NB-LDPC codes based on the iterative soft reliability-based majority-logic decoding (ISRB-MLGD) algorithm. The message shifting is implemented by memories concatenated with variable node units to reduce the area. Although the accumulated soft reliabilities in the ISRB algorithm require longer word length, and accordingly longer critical path and larger memory, the decoder architecture and control logic can be simplified. Particularly, the check node units are modified so that the message switching network can be eliminated. Compared to the iterative hard reliability-based decoder for a (255, 175) NB-LDPC code over GF(28), the proposed ISRB decoder can achieve around 0.8dB coding gain with less than three times hardware complexity.

Asilomar Conference on Signals, Systems and Computers (ACSSC)•Nov 1, 2011•5 citations

Adaptive reliability-based iteration min-sum decoding algorithm for majority-logic decodable LDPC codes

Hongwei Zhao, Kai Zhang, Mengmeng Shi

In this paper, an adaptive decoding algorithm for majority-logic decodable LDPC codes is present based on a recent work by Chen et al. Different from the RBI-MSD algorithm, the presented adaptive reliability-based iteration min-sum decoding algorithm does not need to predesignate the scaling factor, which is optimized by discretized density evolution. In the adaptive RBIMSD algorithm, an adaptive scaling factor is induced for each check node to modify the extrinsic message. The adaptive scaling factor is computed by the ratio of the second minimum and the maximum value among the message, which is received by the check nodes. Simulation results show that, the performance of the adaptive RBI-MSD algorithm is almost as well as that of the original RBI-MSD algorithm but with a little (or negligible) computation increase.

International Conference on Computing, Communication and Networking Technologies (ICCCNT)•Jul 1, 2015•2 citations

Near Optimum Majority-Logic Based Decoding of Low-Density Parity-Check Codes

Telex M. N. Ngatched, Attahiru Sule Alfa, Jun Cai

A reliability-based iterative majority-logic decoding algorithm for regular low-density parity-check (LDPC) codes was recently proposed by Huang et al. In this paper we present an improved version of that algorithm by introducing a different reliability measure for each check-sum of the parity-check matrix, and taking it into account in the computation of the extrinsic information that is used to update the reliability measure of each received bit in each iteration. Some simulations results are given, which show that the new algorithm, while requiring very little additional computational complexity, not only achieves a considerable error performance gain over the standard one, but also, importantly, outperforms the iterative decoding based on belief propagation (IDBP), especially for short and medium block length finite-geometry (FG) LDPC codes.

International Conference on Communications•Jun 1, 2011•3 citations

An efficient majority-logic based message-passing algorithm for non-binary LDPC decoding

Yichao Lu, Nanfan Qiu, Zhixiang Chen +1 more

This paper presents a majority-logic based message-passing algorithm for decoding non-binary LDPC codes. Recently, many majority-logic decoding (MLGD) algorithms make huge efforts on reducing the computational complexity for decoding non-binary LDPC codes. Inspired by one step majority-logic decoding and q-ary sum-product algorithm, we devise a novel iterative double-reliability-based (IDRB) MLGD algorithm which carries out an efficient trade-off between decoding computational complexity and error performance. The proposed algorithm achieves a remarkable enhancement on error correct ability and yet requires only integer operations and finite field operations. Simulation results on two NB-LDPC codes show that we succeed in achieving significant coding gain compared with IHRB- and ISRB-MLGD with limited complexity increase.

IEEE Asia Pacific Conference on Circuits and Systems (APCCAS)•Dec 1, 2012•9 citations
Recently, an iterative soft information reliability-based majority-logic (ISRB-MLG) decoding algorithm was proposed for Euclidean geometry LDPC (EG-LDPC) and Projective geometry LDPC (PG-LDPC) codes. This paper first presents an iterative soft information reliability-based min-sum (ISRB-MS) decoding algorithm based on ISRB-MLG and traditional min-sum decoding algorithm. The performance of ISRB-MS algorithm is greatly improved with a little more complexity than ISRB-MLG algorithm, it mainly needs integer additions and logical operations. Different from traditional min-sum decoding algorithm, the extrinsic information transfer of ISRB-MS algorithm is simplified, we use the full information that all check nodes pass rather than the extrinsic information to update the bit nodes information. Then a modified iterative soft information reliability-based min-sum (MISRB-MS) decoding algorithm is proposed. Compared to (ISRB-MS) algorithm, MISRB-MS algorithm multiplies a scaling factor, so it needs some extra multiplication, but it achieves better performance. Simulation results show that the two algorithms achieve excellent performance and fast convergence rate, they only needs about 10 iterations, if an appropriate scaling factor is chosen, the performance of MISRB-MS algorithm very closes to that of sum-product algorithm (SPA).
Non-binary low-density parity-check (LDPC) codes have some advantages as opposed to their binary counterparts, but unfortunately their decoding complexity is a significant challenge. Hence, the iterative soft-reliability-based (ISRB) majority-logic decoding algorithm is attractive for non-binary LDPC codes, since it involves only finite field additions and multiplications as well as integer additions and comparisons. In this paper, we propose an improved ISRB majority-logic decoding algorithm by using a new reliability update. Our improved algorithm achieves better error performance and faster convergence, while further reducing the computational complexity. For instance, for a (16, 16)-regular (255, 175) cyclic Euclidean geometry LDPC code over GF(28), the proposed algorithm achieves a 0.15 dB coding gain and improves the convergence speed by 10% at a block error rate of 10-4versus the ISRB majority-logic decoding algorithm. Compared with the ISRB majority-logic decoding algorithm, the proposed algorithm requires the same numbers of finite field additions and multiplications but fewer integer additions and comparisons. Furthermore, the ISRB majority-logic decoding algorithm is based on the accumulation of reliability information, and hence the numerical range of the reliability information increases with iterations. In contrast, the proposed reliability update has a fixed numerical range and thus simplifies hardware implementations.
A modified reliability-based iterative majority-logic decoding (MRBI-MLGD) algorithm for two classes of structured LDPC codes is presented based on a recent work by Huang et al. Compared with the original one, the modified algorithm has better performance with slightly increased complexity. Then a reliability-based iterative min-sum decoding (RBI-MSD) algorithm is presented. For the presented RBI-MSD algorithm, reliability-based integer messages are processed and exchanged between variable nodes and check nodes. The main computations include only binary logical operations and integer additions. Different from the conventional min-sum algorithm, the variable nodes pass full messages rather than extrinsic messages to check nodes. This can reduce the memory loads and the computational complexity but with a little (or negligible) performance degradation. Simulation results show that, compared with the (M)RBI-MLGD algorithms, the presented RBI-MSD algorithm achieves better error performance, faster decoding convergence rate and fewer quantization bits with moderate increased computational complexity. Furthermore, the RBI-MSD algorithm is also applicable to decoding random LDPC codes, a distinct difference from the (M)RBI-MLGD algorithms. Finally, we point out that the scaling factors employed in the MRBI-MLGD algorithm and the RBI-MSD algorithm can be optimized using discretized density evolution.
Non-binary low-density parity-check (NB-LDPC) codes have better error-correcting performance than their binary counterparts at the cost of higher decoding complexity when the code length is moderate. Compared to other NB-LDPC decoding algorithms, the iterative reliability-based majority-logic decoding can achieve better performance-complexity tradeoff. In this paper, an efficient partial-parallel shift-message decoder architecture is proposed for cyclic NB-LDPC codes based on the iterative soft reliability-based majority-logic decoding (ISRB-MLGD) algorithm. The message shifting is implemented by memories concatenated with variable node units to reduce the area. Although the accumulated soft reliabilities in the ISRB algorithm require longer word length, and accordingly longer critical path and larger memory, the decoder architecture and control logic can be simplified. Particularly, the check node units are modified so that the message switching network can be eliminated. Compared to the iterative hard reliability-based decoder for a (255, 175) NB-LDPC code over GF(28), the proposed ISRB decoder can achieve around 0.8dB coding gain with less than three times hardware complexity.
In this paper, an adaptive decoding algorithm for majority-logic decodable LDPC codes is present based on a recent work by Chen et al. Different from the RBI-MSD algorithm, the presented adaptive reliability-based iteration min-sum decoding algorithm does not need to predesignate the scaling factor, which is optimized by discretized density evolution. In the adaptive RBIMSD algorithm, an adaptive scaling factor is induced for each check node to modify the extrinsic message. The adaptive scaling factor is computed by the ratio of the second minimum and the maximum value among the message, which is received by the check nodes. Simulation results show that, the performance of the adaptive RBI-MSD algorithm is almost as well as that of the original RBI-MSD algorithm but with a little (or negligible) computation increase.
A reliability-based iterative majority-logic decoding algorithm for regular low-density parity-check (LDPC) codes was recently proposed by Huang et al. In this paper we present an improved version of that algorithm by introducing a different reliability measure for each check-sum of the parity-check matrix, and taking it into account in the computation of the extrinsic information that is used to update the reliability measure of each received bit in each iteration. Some simulations results are given, which show that the new algorithm, while requiring very little additional computational complexity, not only achieves a considerable error performance gain over the standard one, but also, importantly, outperforms the iterative decoding based on belief propagation (IDBP), especially for short and medium block length finite-geometry (FG) LDPC codes.
This paper presents a majority-logic based message-passing algorithm for decoding non-binary LDPC codes. Recently, many majority-logic decoding (MLGD) algorithms make huge efforts on reducing the computational complexity for decoding non-binary LDPC codes. Inspired by one step majority-logic decoding and q-ary sum-product algorithm, we devise a novel iterative double-reliability-based (IDRB) MLGD algorithm which carries out an efficient trade-off between decoding computational complexity and error performance. The proposed algorithm achieves a remarkable enhancement on error correct ability and yet requires only integer operations and finite field operations. Simulation results on two NB-LDPC codes show that we succeed in achieving significant coding gain compared with IHRB- and ISRB-MLGD with limited complexity increase.