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

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

doi:10.1109/tcomm.2012.101712.110709

Cited by 46 publications

(15 citation statements)

References 22 publications

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“…The presorting can not be applied to T-EMS [9] because messages are not sorted nor truncated in the algorithm. However, the presorting can by efficiently applyed to EMS based algrithm [5], simplified EMS [12] and derived implementation derived from EMS as in FB-CN [7], [8] and SB-CN [10].…”

Section: A Presorting To Polarize the Input Messagesmentioning

confidence: 99%

NB-LDPC check node with pre-sorted input

Marchand

Boutillon

2016

2016 9th International Symposium on Turbo Codes and Iterative Information Processing (ISTC)

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Non-binary low-density parity-check codes have better communication performance compared to their binary counterparts but they suffer from higher complexity, especially for the check node processing. In this paper a sorting of the input vectors based on a reliability criteria is performed prior to the check node processing. This presorting process allows the Extended Min-Sum (EMS) check node process to focus its effort mainly on the weakest inputs. Proof is given for a check node of degree 12 in GF(64) for the syndrome based algorithm with a number of computed syndromes reduced by a factor of four which directly impacts the check node complexity without performance degradation.Index Terms-NB-LDPC, Check Node, syndrome-based, EMS.

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Section: A Presorting To Polarize the Input Messagesmentioning

confidence: 99%

NB-LDPC check node with pre-sorted input

Marchand

Boutillon

2016

2016 9th International Symposium on Turbo Codes and Iterative Information Processing (ISTC)

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“…Furthermore, he created the bit flip hard decision decoding algorithm based on the check and statistics as well as proposing the soft decision decoding algorithm based on a posterior probability (APP). The decoding algorithms of multiple LDPC codes are divided into two categories according to the different decision methods [7]: Soft decision algorithm (SDA) and hard decision algorithm (HDA). The representative algorithm of the SDA is the belief propagation (BP) decoding algorithm [8,9].…”

Section: Introductionmentioning

confidence: 99%

Sum of the Magnitude for Hard Decision Decoding Algorithm Based on Loop Update Detection

Meng

Zhao

Tian

et al. 2018

Sensors

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In order to improve the performance of non-binary low-density parity check codes (LDPC) hard decision decoding algorithm and to reduce the complexity of decoding, a sum of the magnitude for hard decision decoding algorithm based on loop update detection is proposed. This will also ensure the reliability, stability and high transmission rate of 5G mobile communication. The algorithm is based on the hard decision decoding algorithm (HDA) and uses the soft information from the channel to calculate the reliability, while the sum of the variable nodes’ (VN) magnitude is excluded for computing the reliability of the parity checks. At the same time, the reliability information of the variable node is considered and the loop update detection algorithm is introduced. The bit corresponding to the error code word is flipped multiple times, before this is searched in the order of most likely error probability to finally find the correct code word. Simulation results show that the performance of one of the improved schemes is better than the weighted symbol flipping (WSF) algorithm under different hexadecimal numbers by about 2.2 dB and 2.35 dB at the bit error rate (BER) of 10−5 over an additive white Gaussian noise (AWGN) channel, respectively. Furthermore, the average number of decoding iterations is significantly reduced.

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“…Several algorithms have been proposed for decoding LDPC codes . Among them, the belief propagation algorithm (BP) has the best performance.…”

Section: Introductionmentioning

confidence: 99%

“…al. proposed a new algorithm for non‐binary LDPC codes named “SMSA” in which changing calculations of the control node simplified the computational complexities of BP but causes dropping in its performance than BP algorithm . The algorithms suggested in the previous studies, speed up the convergence of the BP algorithm, but the performance of this algorithm is not increased in these cases.…”

Section: Introductionmentioning

confidence: 99%

A high‐performance belief propagation decoding algorithm for codes with short cycles

Karimi-lenji

Houshmand

Zarmehi

2017

Int J Communication

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The simplicity of decoding is one of the most important characteristics of the low density parity check (LDPC) codes. Belief propagation (BP) decoding algorithm is a well-known decoding algorithm for LDPC codes. Most LDPC codes with long lengths have short cycles in their Tanner graphs, which reduce the performance of the BP algorithm. In this paper, we present 2 methods to improve the BP decoding algorithm for LDPC codes. In these methods, the calculation of the variable nodes is controlled by using "multiplicative correction factor" and "additive correction factor." These factors are obtained for 2 separate channels, namely additive white Gaussian noise (AWGN) and binary symmetric channel (BSC), as 2 functions of code and channel parameters. Moreover, we use the BP-based method in the calculation of the check nodes, which reduces the required resources. Simulation results show the proposed algorithm has better performance and lower decoding error as compared to BP and similar methods like normalized-BP and offset-BP algorithms.

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

Cited by 46 publications

References 22 publications

NB-LDPC check node with pre-sorted input

NB-LDPC check node with pre-sorted input

Sum of the Magnitude for Hard Decision Decoding Algorithm Based on Loop Update Detection

A high‐performance belief propagation decoding algorithm for codes with short cycles

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