Construction of Near-Optimum Burst Erasure Correcting Low-Density Parity-Check Codes

Chiani, Marco

doi:10.1109/tcomm.2009.05.070047

Cited by 27 publications

(12 citation statements)

References 27 publications

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“…This is because the minimum length of stopping sets determining the burst correcting capability depends on the column order of a parity check matrix. In order to enhance the burst erasure correctability, several heuristic algorithms to improve the column order have been prensend by Wadayama [9], Paolini and Chiani [15], Hosoya et al [8]. Of course, the column order of a parity check matrix does not affect the decoding performance over memoryless erasure channels.…”

Section: Introductionmentioning

confidence: 99%

Band Splitting Permutations for Spatially Coupled LDPC Codes Achieving Asymptotically Optimal Burst Erasure Immunity

Mori

Wadayama

2017

IEICE Trans. Fundamentals

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It is well known that spatially coupled (SC) codes with erasure-BP decoding have powerful error correcting capability over memoryless erasure channels. However, the decoding performance of SC-codes significantly degrades when they are used over burst erasure channels. In this paper, we propose band splitting permutations (BSP) suitable for (l, r, L) SC-codes. The BSP splits a diagonal band in a base matrix into multiple bands in order to enhance the span of the stopping sets in the base matrix. As theoretical performance guarantees, lower and upper bounds on the maximal burst correctable length of the permuted (l, r, L) SC-codes are presented. Those bounds indicate that the maximal correctable burst ratio of the permuted SC-codes is given by λmax ≃ 1/k where k = r/l. This implies the asymptotic optimality of the permuted SC-codes in terms of burst erasure correction.

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Section: Introductionmentioning

confidence: 99%

Band Splitting Permutations for Spatially Coupled LDPC Codes Achieving Asymptotically Optimal Burst Erasure Immunity

Mori

Wadayama

2017

IEICE Trans. Fundamentals

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“…3) using simple column swaps or variable-node permutations (swaps) to achieve or approach the concatenated channel capacity or threshold bounds. The enhanced codes are constructed from the following permutation methods: the greedy search and swap (GSS) algorithm [5], the pivot searching and swapping (PSS) method in [6], and the simulated annealing (SA) approach in [7]. We plot the codes performances on the concatenated channels with increasing q values.…”

Section: Ldpc Code Performancementioning

confidence: 99%

Channels with both random errors and burst erasures: Capacities, LDPC code thresholds, and code performances

Kavcic

Venkataramani

et al. 2010

2010 IEEE International Symposium on Information Theory

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Abstract-We derive the capacities of a class of channels, either memoryless or indecomposable finite-state, that also suffer from bursts of erasures. For such channels, we analyze the performances of low-density parity-check (LDPC) codes and code ensembles under belief propagation (BP) decoding, using density evolution (DE) techniques. Although known LDPC codes perform well in non-erasure-affected channels, their performances are far from the capacities when both random errors and erasures are present. We show that enhancing the codes' erasure handling using published methods beats, in some instances, the BP thresholds. However, to achieve capacity, codes must be constructed to tackle both effects simultaneously.

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“…The metric here adopted to measure the code capability to exploit erasure correlation is the MTBL. An effective algorithm, proposed in [9], to improve the MTBL of a given LDPC code is reviewed next.…”

Section: B Geira Codesmentioning

confidence: 99%

On Construction of Moderate-Length LDPC Codes over Correlated Erasure Channels

Liva

Matuz

Katona

et al. 2009

2009 IEEE International Conference on Communications

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The design of moderate-length erasure correcting low-density parity-check (LDPC) codes over correlated erasure channels is considered. Although the asymptotic LDPC code design remains the same as for a memoryless erasure channel, robustness to the channel correlation shall be guaranteed for the finite length LDPC code. This further requirement is of great importance in several wireless communication scenarios where packet erasure correcting codes represent a simple countermeasure for correlated fade events (e.g., in mobile wireless broadcasting services) and where the channel coherence time is often comparable with the code length. In this paper, the maximum tolerable erasure burst length (MTBL) is adopted as a simple metric for measuring the code robustness to the channel correlation. Correspondingly, a further step in the code construction is suggested, consisting of improving the LDPC code MTBL. Numerical results conducted over a Gilbert erasure channel, under both iterative and maximum likelihood decoding, highlight both the importance of the MTBL improvement in the finite-length code construction and the possibility to tightly approach the performance of maximum distance separable codes.

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Construction of Near-Optimum Burst Erasure Correcting Low-Density Parity-Check Codes

Cited by 27 publications

References 27 publications

Band Splitting Permutations for Spatially Coupled LDPC Codes Achieving Asymptotically Optimal Burst Erasure Immunity

Band Splitting Permutations for Spatially Coupled LDPC Codes Achieving Asymptotically Optimal Burst Erasure Immunity

Channels with both random errors and burst erasures: Capacities, LDPC code thresholds, and code performances

On Construction of Moderate-Length LDPC Codes over Correlated Erasure Channels

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