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Journal of Computer Applications

Analysis and improvement of the bit-flipping decoding algorithm for LDPC codes

SU Guang-chuan

Published Jan 1, 2006• 0 citations
OpenAlex

Abstract

According to the statistical decoding method,a new enlarged set of the low density check vectors was constructed by the linear combination among the vectors of the LDPC code's old check matrix.Combined with the analysis of the ParallelBit-Flipping(PBF) decoding algorithm,such as loop detection technique,a new hard-decision decoding algorithm was presented for LDPC codes.The simulation results show that our algorithm has small iterative numbers just like the PBF algorithm,and the decoding performance approaching the belief propagation algorithm.

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According to the statistical decoding method,a new enlarged set of the low density check vectors was constructed by the linear combination among the vectors of the LDPC code's old check matrix.Combined with the analysis of the ParallelBit-Flipping(PBF) decoding algorithm,such as loop detection technique,a new hard-decision decoding algorithm was presented for LDPC codes.The simulation results show that our algorithm has small iterative numbers just like the PBF algorithm,and the decoding performance approaching the belief propagation algorithm.
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.
In this paper, we introduce a new bit-flipping decoding algorithm for low-density parity-check codes based on loop detection mechanism, which is an extension to soft-decision decoding. This decoding algorithm's performance has been significantly improved by introducing a loop detection mechanism for the failed flipping bit and leading into the soft-decision about the reliability measure of the received symbols. Theoretical analysis shows that the complexity of this algorithm is lower. Some simulation results are given, which show that compared with other known kinds of bit-flipping decoding algorithms for LDPC codes, this new decoding on the additive white Gaussian noise channel offer excellent performance.
In this paper, an improved belief propagation decoding algorithm was proposed for low density parity check codes. In the proposed decoding process, error bits can be detected once again after hard-decision in the conventional BP decoding algorithm. The detection criterion is based on check matrix characteristics and D-value between prior probability and posterior probability. Simulation results demonstrate the performance of the improved BP decoding algorithm outperform that of the conventional BP decoding algorithm.
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.
In this paper, a new low-complexity symbol-flipping algorithm to decode nonbinary low-density parity-check (LDPC) codes is proposed. The decoding procedure updates iteratively the hard-decision received symbol vector in search of a valid codeword in the symbol vector space. Only one symbol is changed in each iteration, and symbol flipping function combines the number of failed checks and reliability of the received bits and calculated symbols. An optional mechanism to avoid infinite loops in high Galois field search is also proposed. Our studies show that the algorithm achieves an appealing tradeoff between performance and complexity over relatively low Galois field for short to medium code length.