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International Conference on Advanced Communication Technology

Simple improvements of bit-flipping decoding

Hiroshi Kamabe, Shusaku Kobota

Published Jan 1, 2010• 4 citations
OpenAlex

Abstract

A bit-flipping (BF) algorithm is a decoding algorithm for LDPC codes that can be efficiently implemented by electronic circuits. Although its error correcting performance is rather poor, we show that a BF algorithm with bias terms has good error correcting performance. We also introduce two more parameters to improve the performance further. We also propose a variant of candidate bit based BF (CBBF) algorithm by introducing bias terms. We see that these algorithms having bias terms exhibit very good error correcting performances.

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A bit-flipping (BF) algorithm is a decoding algorithm for LDPC codes that can be efficiently implemented by electronic circuits. Although its error correcting performance is rather poor, we show that a BF algorithm with bias terms has good error correcting performance. We also introduce two more parameters to improve the performance further. We also propose a variant of candidate bit based BF (CBBF) algorithm by introducing bias terms. We see that these algorithms having bias terms exhibit very good error correcting performances.
In order to improve the bit-flipping (BF) decoding algorithms, a weighted hard-decision based BF decoding algorithm for low-density parity-check (LDPC) codes is presented, in which the weights of variable-nodes are employed. A new metric is defined for the weight of candidate bits not only in unsatisfied parity check equations but also in satisfied ones. The connection between min-sum decoding algorithm and the proposed algorithm is presented. Simulation results show that the new decoding algorithm can provide better FER performance and faster convergence speed than the original candidate bit based bit-flipping (CBBF) algorithm.
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.
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, 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.
A new class of iterative bit flipping (BF) decoding algorithms adapted for low-density parity check (LDPC) convolutional codes is proposed. Compared with Gallager's original BF algorithm, the new BF algorithms improve both the coding gain and the error correction speed. At a bit error rate (BER) of 10 , the best of the new bit-flipping algorithms achieves, after only 6 iterations and with much simpler decoding hardware, a coding gain within 3.5 dB of that of the conventional min-sum belief propagation decoding algorithm.
The Bit-Flipping (BF) algorithm is considered as a hard decoding method for LDPC codes. It is much simpler than the probabilistic methods like Sum Product Algorithm (SPA), and can be efficiently implemented by electronic circuits. In this paper, we propose a new Bit Flipping algorithm for Low-Density Parity-Check codes (LDPC) called Single Bit-Flipping (SBF). Compared to the Gallager Bit-Flipping algorithm, the proposed algorithm employs criteria of flipping single bit chosen carefully. This method eliminates the risk for flipping more than one bit at a time that can induce additional error bits and propagate the errors to the later iterations. We present some results obtained by applying this new method that provides a gain in performance in comparison to the standard Gallager Bit-Flipping with low complexity.