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International Journal of Computer Theory and Engineering

n Improved Multi-Bit Threshold Flipping LDPC Decoding Algorithm

Lina Zhang, Zhihui Ye, Qi Feng

Published May 5, 2014• 4 citations
Publisher
DOI
10.7763/ijcte.2014.v6.919

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A novel bit-flipping (BF) decoding algorithm is proposed for structured low-density parity-check (LDPC) codes. The proposed BF algorithm which is called multi-threshold bit-flipping (MTBF) algorithm, flips multiple bits by using multiple thresholds at each iteration. It only requires some real operations before iterations and requires only logical operations during the iterations. The MTBF algorithm has lower complexity than the weighted bit-flipping algorithm and its modifications. Simulations show that the proposed algorithm has fast convergence speed and good performance.
In this paper, a new two-stage hybrid algorithm for decoding Low-Density Parity-Check (LDPC) codes is proposed that incorporates two iterative decoding. For the first stage of decoding, we offer a new decoding algorithm called Improved Variable Multi Weighted Bit-Flipping (IVMWBF) algorithm. Since the IVMWBF algorithm is based on the idea of flipping variable multi bits in each iteration, both improvement in performance and reduction in iteration number and computational complexity are observed in this algorithm. The proposed hybrid algorithm which is a combination of the IVMWBF and BP algorithms, while having a performance exactly similar to that of the BP algorithm, has less complexity compared to that algorithm.
Gradient descent bit flipping (GDBF) algorithm is an important low-complexity method for decoding LDPC codes. In particular, the multi-bit GDBF decoding has the best decoding performance among BF algorithms if a suitable threshold is prescribed. However, extensive computer searches are needed to find such a threshold for a specific LDPC code. In this paper, we propose a syndrome-aided GDBF (SAGDBF) algorithm to address the problem. The thresholds in our algorithm are adaptively adjusted according to the syndrome values in the iterative process. Simulation results for different LDPC codes suggest that the error performances of the proposed SAGDBF algorithm are close to and even better than the original multi-bit GDBF algorithm at a relatively small number of iterations. In addition, the complexity increased in our proposed algorithm is negligible compared with the original multi-bit GDBF algorithm. Hence, the proposed algorithm is suitable for practical purposes.