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arXiv:1001.2503

Check Reliability Based Bit-Flipping Decoding Algorithms for LDPC Codes

Chi-Yuan Chang, Yu T. Su, Chen, Yu-Liang, Yin-Chen Liu

Published Jan 14, 2010• 5 citations
arXivHTMLPDF

Abstract

We introduce new reliability definitions for bit and check nodes. Maximizing global reliability, which is the sum reliability of all bit nodes, is shown to be equivalent to minimizing a decoding metric which is closely related to the maximum likelihood decoding metric. We then propose novel bit-flipping (BF) decoding algorithms that take into account the check node reliability. Both hard-decision (HD) and soft-decision (SD) versions are considered. The former performs better than the conventional BF algorithm and, in most cases, suffers less than 1 dB performance loss when compared with some well known SD BF decoders. For one particular code it even outperforms those SD BF decoders. The performance of the SD version is superior to that of SD BF decoders and is comparable to or even better than that of the sum-product algorithm (SPA). The latter is achieved with a complexity much less than that required by the SPA.

DOI
10.48550/arxiv.1001.2503

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We introduce new reliability definitions for bit and check nodes. Maximizing global reliability, which is the sum reliability of all bit nodes, is shown to be equivalent to minimizing a decoding metric which is closely related to the maximum likelihood decoding metric. We then propose novel bit-flipping (BF) decoding algorithms that take into account the check node reliability. Both hard-decision (HD) and soft-decision (SD) versions are considered. The former performs better than the conventional BF algorithm and, in most cases, suffers less than 1 dB performance loss when compared with some well known SD BF decoders. For one particular code it even outperforms those SD BF decoders. The performance of the SD version is superior to that of SD BF decoders and is comparable to or even better than that of the sum-product algorithm (SPA). The latter is achieved with a complexity much less than that required by the SPA.
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.
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.
This paper presents a novel iterative reliability-based bit flipping (BF) algorithm for decoding low-density parity-check codes. The new decoder is a single BF algorithm called two-round selection -based bit flipping. It introduces the idea of a two-round selection of the flipped bit, based successively on hard and soft received channel values. In the first stage, a set of unreliable bits is identified, and then a second selection is used, to pick out among them the bit to flip. In the second round of selection, the initial belief about received signals, contributes efficiently to selecting the best candidate bit. We demonstrate through simulations over the binary-input additive white Gaussian noise channel and the Rayleigh fading channel that the proposed algorithm exhibits better decoding performance when compared with some well-known soft decision BF algorithms. A complexity analysis of the proposal and a comparison to other BF decoders are also presented.
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.
A hard-decision decoding algorithm based on parity-check sum for LDPC code was first described, and then a soft-decision decoding algorithm based on parity-check sum and symbol reliability was proposed. The soft-decision decoding algorithm incorporates received symbol reliability information and a simple taboo function that avoids repeated flipping of the same bit. A maximum votes queue algorithm for the numbers of which the parity-check functions were not satisfied was applied to quickly search the flipping bit. Approaches above all were used to improve the performance of the flipping-bit algorithm based on parity-check sum.
Bit-flipping (BF) decoding of low-density parity-check codes is of low complexity but gives inferior performance in general. To improve performance and provide new BF decoder options for complexity-performance tradeoffs, we propose new designs for the flipping function (FF), the flipped bit selection (FBS) rule and the checksum weight updating schedule. The new FF adjusts the checksum weights in every iteration while our FBS rules take more information into account. These two modifications represent efforts to track more closely the evolutions of both check and variable nodes' reliabilities. Two selective update schedules are proposed to offer more performance and complexity tradeoffs. The combinations of the new FBS rule and known FFs result in new BF decoders with improved performance and a modest complexity increase. On the other hand, combining the new FF and FBS rule gives a new decoder with performance comparable to that of the normalized min-sum algorithm while if we use a much simpler FBS rule instead, the decoder suffers little performance loss with reduced complexity. We also present a simple decision-theoretical argument to justify the new checksum weight formula and a time-expanded factor graph model to explain the proposed selective weight-updating schedules.