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IEEE International Symposium on Information Theory (ISIT)

Candidate bit based bit-flipping decoding algorithm for LDPC codes

Guiqiang Dong, Yanan Li, Ningde Xie, Tong Zhang, Huaping Liu

Published Jun 1, 2009• 11 citations
Publisher

Abstract

A novel hard-decision decoding algorithm for low-density parity-check (LDPC) codes is proposed in this paper. This algorithm employs the correlation information among the column vectors of the parity-check matrix and syndrome vector for decoding. It does not require soft information, and has low decoding complexity. Simulation results show that the proposed decoding algorithm could provide an effective tradeoff between error performance and decoding complexity.

DOI
10.1109/isit.2009.5205798

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A novel hard-decision decoding algorithm for low-density parity-check (LDPC) codes is proposed in this paper. This algorithm employs the correlation information among the column vectors of the parity-check matrix and syndrome vector for decoding. It does not require soft information, and has low decoding complexity. Simulation results show that the proposed decoding algorithm could provide an effective tradeoff between error performance and decoding complexity.
An improved bit-flipping decoding algorithm is proposed for low-density parity-check(LDPC) codes in this paper.Two influences on error probabilities of code bits are considered: the influence of the number of code bits included in an unsatisfied check,and the influence of the number of unsatisfied checks of each code bit.No soft information is required for decoding.Simulation results show that improvement on performance is observed for the proposed algorithm,and it provides better performance over several soft-decision bit-flipping decoding algorithms for LDPC codes with large girth.
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In this letter, a low complexity decoding algorithm for binary linear block codes is applied to low-density paritycheck (LDPC) codes and improvements are described, namely an extension to soft-decision decoding and a loop detection mechanism. For soft decoding, only one real-valued addition per code symbol is needed, while the remaining operations are only binary as in the hard decision case. The decoding performance is considerably increased by the loop detection. Simulation results are used to compare the performance with other known decoding strategies for LDPC codes, with the result that the presented algorithms offer excellent performances at smaller complexity.
This paper proposes a modified weighted violation-based bit-flipping decoding algorithm for LDPC codes, and no soft information is required for decoding, Futhermore, in order to reduce the average number of iterations and decoding complexity, the threshold of judgement is set. Simulation results show that this modified algorithm could achieve much less number of iterations and better performance as compared with several soft-decision bit-flipping decoding algorithms for LDPC codes with large girth and low code rate.
In this paper, a new method for improving hard-decision bit-flipping (BF) decoding is proposed for low-density parity-check codes. The flipping criterion is derived theoretically from the soft-decision belief-propagation decoding algorithm. The proposed BF decoding algorithm is channel independent and is improved by introducing a more efficient method for computing the reliability of the parity checks. Extensive simulations are provided to demonstrate the efficiency of the proposed algorithm. Simulation results show that the proposed algorithm can achieve about 1.5dB coding gain improvement at BER = 5×10−6while reducing up to 48% iterations for decoding and maintaining low decoding complexity, compared with the conventional weighted BF algorithm.
It is proved that hard decision algorithms are more appropriate than a soft decision for low-density parity-check (LDPC) decoding since they are less complex at the decoding level. On the other hand, it is notable that the soft decision algorithm outperforms the hard decision one in terms of the bit error rate (BER) gap. In order to minimize the BER and the gap between these two families of LDPC codes, a new LDPC decoding algorithm is suggested in this paper, which is based on both the normalized min-sum (NMS) and modified-weighted bit-flipping (MWBF). The proposed algorithm is named normalized min sum- modified weighted bit flipping (NMSMWBF). The MWBF is executed after the NMS algorithm. The simulations show that our algorithm outperforms the NMS in terms of BER at 10-8 over the additive white gaussian noise (AWGN) channel by 0.25 dB. Furthermore, the proposed NMSMWBF and the NMS are both at the same level of decoding difficulty.