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International Conference on Signal Processing Systems (ICSPS)

Improved syndrome-based ordered statistic decoding algorithm for LDPC codes

Dong Zijian, Liu Fei, Song Yaolian

Published Jul 1, 2010• 2 citations
Publisher

Abstract

Ordered statistics decoding (OSD) algorithm and syndrome-based decoding algorithm are investigated in this work, based on which, a syndrome-based ordered statistics decoding (SOSD) algorithm for LDPC codes is proposed. The indexed systematic form of parity check matrix is obtained based on the least reliable independent positions (LRIPs) by performing Gaussian eliminations, which promises that the SOSD processing need not the re-encoding process, but only several binary vector additions, therefore achieves noticeable computation complexity reduction.

DOI
10.1109/icsps.2010.5555626

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Ordered statistics decoding (OSD) algorithm and syndrome-based decoding algorithm are investigated in this work, based on which, a syndrome-based ordered statistics decoding (SOSD) algorithm for LDPC codes is proposed. The indexed systematic form of parity check matrix is obtained based on the least reliable independent positions (LRIPs) by performing Gaussian eliminations, which promises that the SOSD processing need not the re-encoding process, but only several binary vector additions, therefore achieves noticeable computation complexity reduction.
A syndrome-based ordered statistics decoding(SOSD) algorithm for LDPC codes is proposed based on ordered statistics decoding(OSD) algorithm and syndrome-based decoding algorithm.The indexed systematic form of parity check matrix is obtained based on the least reliable independent positions(LRIPs) by performing Gaussian eliminations,which leads to that candidate codes are generated in the SOSD processing by using several binary vector additions,instead of using the re-encoding process,computation complexity in thereby reduced.A block accumulated log-likelihood ratio(LLR) strategy is further proposed to reconstruct the ordered information sequence,which can reduce the sensitivity of accumulated parameter selection to performance fluctuation.
In this paper, we propose an efficient decoding algorithm for short low-density parity check (LDPC) codes by carefully combining the belief propagation (BP) decoding and ordered statistics decoding (OSD) algorithms. Specifically, a modified BP (mBP) algorithm is applied for a certain number of iterations prior to OSD to enhance the reliability of the received message, where an offset parameter is utilized in mBP to control the weight of the extrinsic information in message passing. By carefully selecting the offset parameter and the number of mBP iterations, the number of errors in the most reliable positions (MRPs) in OSD can be reduced by mBP, thereby significantly improving the overall decoding performance of error rate and complexity. Simulation results show that the proposed algorithm can approach the maximum-likelihood decoding (MLD) for short LDPC codes with only a slight increase in complexity compared to BP and a significant decrease compared to OSD. Specifically, the order- (m -1) decoding of the proposed algorithm can achieve the performance of the order-m OSD.
Aiming at bridge gap between maximum likelihood decoding (MLD) and belief propagation (BP) decoding for short or medium LDPC codes, we present one modified ordered statistics decoding (OSD) reprocessing method, which is serially concatenated with standard BP. Meanwhile, two novel points in implementation are addressed. For one thing, the new definition of bit reliability proposed enhances error-correcting performance via centralizing more decoding errors of standard BP within the scope of order-p OSD where p ≤ 2. For another, one way of reducing computational complexity is put forward in selecting optimal error pattern among all candidates. Simulation results demonstrate our approach could achieve good tradeoff between reprocessing performance and computational complexity. Techniques on further improvement are also discussed briefly. Reliability-based syndrome decoding of LDPC codes 1 I.
Abstract Aimed at bridging the gap between the maximum likelihood and the suboptimal decoding schemes for short or medium LDPC codes, a generalised ordered statistic decoding (OSD), in the form of syndrome decoding, is presented in the paper. The OSD is invoked once when a nonzero decoding syndrome is returned for the preceded belief propagation (BP) or min‐sum (MS) variants. With respect to the OSD with an accumulative reliability metric for the BP in the logarithmic likelihood ratio (LLR) domain, we extend the metric to the BP in the probability domain. Furthermore, the OSD with the metric specific for the MS variants, shows an appealing trade‐off between performance and complexity. Meanwhile, when determining the optimal error pattern estimation, an alternative designed to reduce the number of the required real additions proves to be effective. Copyright © 2008 John Wiley & Sons, Ltd.
Aiming at bridging the gap between the maximum likelihood decoding (MLD) and the suboptimal iterative decodings for short or medium length LDPC codes, we present a generalized ordered statistic decoding (OSD) in the form of syndrome decoding, to cascade with the belief propagation (BP) or enhanced min-sum decoding. The OSD is invoked only when the decoding failures are obtained for the preceded iterative decoding method. With respect to the existing OSD which is based on the accumulated log-likelihood ratio (LLR) metric, we extend the accumulative metric to the situation where the BP decoding is in the probability domain. Moreover, after generalizing the accumulative metric to the context of the normalized or offset min-sum decoding, the OSD shows appealing tradeoff between performance and complexity. In the OSD implementation, when deciding the true error pattern among many candidates, an alternative proposed proves to be effective to reduce the number of real additions without performance loss. Simulation results demonstrate that the cascade connection of enhanced min-sum and OSD decodings outperforms the BP alone significantly, in terms of either performance or complexity.
Irregular Low-Density Parity-Check (LDPC) codes generally achieve better performance than regular LDPC codes at low E b /N 0 values. They have, however, higher error floors than regular LDPC codes. With respect to the construction of the irregular LDPC code, it can achieve the trade-off between the performance degradation of low E b /N 0 region and lowering error floor. It is known that a decoding algorithm can achieve very good performance if it combines the Ordered Statistic Decoding (OSD) algorithm and the Log Likelihood Ratio-Belief Propagation (LLR-BP) decoding algorithm. Unfortunately, all the codewords obtained by the OSD algorithm satisfy the parity check equation of the LDPC code. While we can not use the parity check equation of the LDPC code to stop the decoding process, the wrong codeword that satisfies the parity check equation raises the error floor. Once a codeword that satisfies the parity check equation is generated by the LLR-BP decoding algorithm, we regard that codeword as the final estimate and halt decoding; the OSD algorithm is not performed. In this paper, we propose a new encoding/decoding scheme to lower the error floor created by irregular LDPC codes. The proposed encoding scheme encodes information bits by Cyclic Redundancy Check (CRC) and LDPC code. The proposed decoding scheme, which consists of the LLR-BP decoding, CRC check, and OSD decoding, detects errors in the codewords obtained by the LLR-BP decoding algorithm and the OSD decoding algorithm using the parity check equations of LDPC codes and CRC. Computer simulations show that the proposed encoding/decoding scheme can lower the error floor of irregular LDPC codes.