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IEEE Communications Letters

Hard-Decision Bit-Flipping Decoder Based on Adaptive Bit-Local Threshold for LDPC Codes

Yuanhua Liu, Meiling Zhang

Published Apr 4, 2019• 18 citations
Publisher

Abstract

This letter presents two novel adaptive bit-local threshold bit-flipping algorithms for improving the hard-decision decoding performance of LDPC codes. The threshold of each bit can be changed adaptively to maximize the number of corrected errors during the iterations. The proposed methods require only logical operations during decoding and can be realized easily by hardware. Compared with the existing adaptive threshold BF algorithm, the proposed algorithms achieve better performance while removing the need for the delay-inducing global maximum operations, thus facilitating high-throughput decoding.

DOI
10.1109/lcomm.2019.2909207

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This letter presents two novel adaptive bit-local threshold bit-flipping algorithms for improving the hard-decision decoding performance of LDPC codes. The threshold of each bit can be changed adaptively to maximize the number of corrected errors during the iterations. The proposed methods require only logical operations during decoding and can be realized easily by hardware. Compared with the existing adaptive threshold BF algorithm, the proposed algorithms achieve better performance while removing the need for the delay-inducing global maximum operations, thus facilitating high-throughput decoding.
The bit-flipping (BF) algorithm for decoding of low-density parity-check (LDPC) codes requires less complex hardware than other decoding algorithms, but its error correcting performance needs to be improved. In this letter, a threshold adaptation scheme is applied to BF algorithm based decoding of LDPC codes. Our experiments show that the optimal threshold value for BF depends on the error conditions, and threshold adjustment during decoding helps to prevent meaningless no-flipping iterations. Based on these statistical observations, the adaptive threshold technique is proposed to pursue both the maximum error correcting capability and the fastest decoding convergence.
In this paper, we present a novel bit flipping algorithm for high-throughput decoding of LDPC codes. The algorithm exploits the turbo principle to reduce the average number of iterations and employs a bit-local thresholding operation to remove the need for a block-wise minimum operation — which is common to many conventional bit flipping decoders — that hinders decoder throughput. Through simulations the proposed decoder is shown to achieve comparable bit-error rate performance to state-of-the-art techniques while requiring approximately half the number of iterations on average thus facilitating high-throughput decoding.
An improved iterative bit-flipping(BF) algorithm adapted for decoding low-density parity-check(LDPC) codes is proposed to improve the performance of the hard-decision BF decoding algorithm.The new algorithm uses an alternating threshold pattern to determine the bits whether to be flipped or not,and the flipping error probability is effectively decreased.Simulation results show that compared with BF algorithm,the improved BF algorithm improves both the error-correction performance and the convergence speed while maintaining the low computational complexity.
An improved bit-flipping(BF) algorithm with low complexity for decoding structured low-density parity-check codes(LDPC) is proposed to improve the performance of the hard-decision BF algorithm.The hard-decision bits are divided into two groups based on the magnitudes of the received symbols,and at each iteration,the proposed algorithm can flip more than one bit with using two thresholds,and the flipping error probability is effectively decreased.The improved BF algorithm requires some real number comparisons before iterations and requires only logical operations during the iterations.Compared with the weighted bit-flipping algorithm and its modifications,the new method is with significantly lower complexity.Simulations show that the proposed algorithm is provided with very fast convergence speed and excellent performance with significantly low complexity.
A novel bit-flipping (BF) algorithm with low complexity for high-throughput decoding of low-density parity-check (LDPC) codes is presented. At each iteration, a novel threshold pattern is used to determine the code bits whether to be flipped or not, and the flipping error probability is effectively decreased. Compared with the weighted BF algorithm and its modifications, the modified BF algorithm has significantly lower complexity and decoding time. Through simulations the proposed BF algorithm is shown to achieve excellent performance and fast convergence speed while maintaining significantly low complexity thus facilitating high-throughput decoding.
We present two general multi-stage (MS) bit-flipping (BF) decoding algorithms for low-density parity-check (LDPC) codes. Both algorithms consist of soft-decision (SD) and hard-decision BF decoding parts. In comparison with known MS LDPC decoders, our approach is much simpler as all stages share the same BF structure. The only complexity increase is due to the use of an adaptive stage-switching (SS) mechanism which gives near-optimal SS timing. A new design issue we address is that the first-stage algorithm's parameter has to be re-tuned to achieve the optimal overall performance. The numerical results demonstrate that the proposed decoding methods can significantly improve the error-rate performance of the conventional SD BF decoders.