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In this study, a new method for improving hard-decision bit-flipping (BF) decoding is proposed for low-density paritycheck 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 1.6 dB coding gain improvement at BER = 10-5 while reducing up to 53% iterations for decoding and maintaining low-decoding complexity, compared with the conventional weighted BF algorithm. [ABSTRACT FROM AUTHOR]

This study proposes a new low-complexity decoding algorithm for low-density parity check codes, which is a variation of the offset min-sum algorithm and achieves a similar performance with lower hardware cost. A finite precision study is presented and the hardware cost of the implementation of three very large scale integration architectures is evaluated. As a conclusion, the proposed algorithm achieves similar performance with an area saving of around 18, 10 and 14% for the memory-based partially parallel, fully parallel and sliced message passing implementations, respectively. [ABSTRACT FROM AUTHOR]

In this study, the authors propose an improved version of the min-sum algorithm for low-density parity check code decoding, which the authors call 'adaptive normalised BP-based' algorithm. Their decoder provides a compromise solution between belief propagation and the min-sum algorithms by adding an exponent offset to each variable node's intrinsic information in the check node update equation. The extrinsic information from the min-sum decoder is then adjusted by applying a negative power of the two scale factor, which can be easily implemented by right shifting the min-sum extrinsic information. The difference between their approach and other adaptive normalised min-sum decoders is that the authors select the normalisation scale factor using a clear analytical approach based on the underlying principles. The simulation results show that the proposed decoder outperforms the min-sum decoder and performs very close to the BP decoder with lower complexity. [ABSTRACT FROM AUTHOR]

A doubly multistage decoder (DMD) for low-density parity-check codes over ℤ2m, m > 1, which fuses the multistage decoding approaches of Armand et al. and Varnica et al., is proposed. Two variants of the DMD are considered. The first (respectively, second) performs belief-propagation (BP) [respectively, offset min-sum (OMS)] decoding in each decoding stage and is referred to as DMD -- BP (respectively, DMD -- OMS). For the moderate-length codes considered in this study, the computer simulations show the DMD -- BP (respectively, DMD -- OMS) achieving coding gains of up to 0.43 dB (respectively, 0.67 dB) over standard BP decoding at a bit error rate of 10-6 on an additive-white-Gaussian-noise channel, while requiring significantly less computational power. Remarkably, DMD -- OMS outperforms DMD -- BP, yet has lower computational complexity than DMD -- BP. Snapshots of the log-likelihood ratio densities of the decoded bits midway through the decoding process explain the superiority of the DMD over standard BP decoding. [ABSTRACT FROM AUTHOR]