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

Jin Xie, Liuguo Yin, Ning Ge, Jianhua Lü

Published May 20, 2009• 1 citation

Abstract

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%.

Related papers

Fast convergence algorithm for decoding of low density parity check codes

Jin Xie, Liuguo Yin, Ning Ge +1 more

Abstract: In this paper, a fast-convergence algorithm is proposed for the decoding of low-density parity-check (LDPC) codes. By putting more weight on the message update from check node to variable node in current iteration, the proposed method speeds up the decoding significantly. Simulation results show that compared with the standard layered min-sum decoding algorithm, the proposed scheme may reduce about 1/6 iteration numbers for LDPC codes used in DVB-S2, with hardware complexity overhead less than 2%. Key–Words: LDPC code, fast convergence decoding algorithm, layered decoding, min-sum algorithm, hardware implementation 1

WSEAS TRANSACTIONS on COMMUNICATIONS archiveJul 1, 20091 citation

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 SecurityJun 1, 20109 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, 20210 citations

An optimized min-sum variable node layering for LDPC decoding

Nassib Laouini, Larbi Ben Hadj Slama, Ammar Bouallègue

Layered decoding is well appreciated in Low-Density Parity-Check (LDPC) decoder implementation since it provides efficient and high-throughput implementation of LDPC decoders. Variable-Node Layered Belief Propagation (VL-BP) algorithm and their reduced-complexity derivatives for LDPC codes are presented. The VL-BP algorithm is a modification of Belief Propagation algorithm (BP), where the variable nodes are divided in subgroups called layers and each iteration is broken into multiple sub-iterations. Some simplifications can also be made to lower the complexity of both BP and CL-BP algorithms, and particularly the complexity of the check node update rule. In this paper, we consider Variable Node Layered BP (VL-BP) algorithm and propose an optimized min-sum VL-BP (MS VL-BP) algorithm for decoding LDPC code which has better performance not only from MS VL-BP algorithm but also from BP algorithm. In this decoding method, unlike other layered algorithms, we consider for the first layer a set of variable nodes that has a low value of the intrinsic information. Simulation results show that good performance can be achieved, and which can even be improved by the addition of either a normalization term or an additive offset term.

Apr 1, 20141 citation

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, 20231 citation

Improved Layered Minimum Sum Decoding Algorithm Based on Overestimation

Liu Yu, Lin Bai, Yaohui Hao

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.

Sep 23, 20220 citations