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International Multi-Conference on Engineering, Computer and Information Sciences (SIBIRCON)

Burst Detection and Correction for Gilbert Codes and its QC-LDPC Extensions

Вересова Алина Максимовна, Andrei A. Ovchinnikov

Published Sep 30, 2024• 2 citations
Publisher

Abstract

The article discusses the issue of determining the location of an error burst based on the structure of a block-permutation low-density parity-check code. Quasi-cyclic low-density parity-check codes with a small number of blocks are considered, making it possible to correct the longest possible bursts within this construction. Through experimentation, the maximum, minimum, and average number of attempts was estimated when determining the start position of the error burst. The features of determining the location of a packet in block-permutation low-density parity-check codes are revealed. The proposed method is based on using majority decoding techniques and allows reducing the average number of attempts to locate a burst from hundreds to units for the codes under consideration. Using the packet detection method, which is based on the analysis of the structure of the parity-check matrix, algorithms for decoding Gilbert and extended Gilbert codes have been proposed, ensuring the correction of bursts within their error-correction capabilities. The process of decoding extended Gilbert codes utilizes list decoding in a supercode, with a criterion for selecting the error vector based on the syndrome.

DOI
10.1109/sibircon63777.2024.10758475

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IEEE International Symposium on Information Theory (ISIT)•Jul 1, 2008•8 citations
The article discusses the issue of determining the location of an error burst based on the structure of a block-permutation low-density parity-check code. Quasi-cyclic low-density parity-check codes with a small number of blocks are considered, making it possible to correct the longest possible bursts within this construction. Through experimentation, the maximum, minimum, and average number of attempts was estimated when determining the start position of the error burst. The features of determining the location of a packet in block-permutation low-density parity-check codes are revealed. The proposed method is based on using majority decoding techniques and allows reducing the average number of attempts to locate a burst from hundreds to units for the codes under consideration. Using the packet detection method, which is based on the analysis of the structure of the parity-check matrix, algorithms for decoding Gilbert and extended Gilbert codes have been proposed, ensuring the correction of bursts within their error-correction capabilities. The process of decoding extended Gilbert codes utilizes list decoding in a supercode, with a criterion for selecting the error vector based on the syndrome.
When transmitting information over channels with grouping errors, the traditional approach is channel decorrelation and use of codes correcting independent errors. The decorrelation procedure lowers achievable rates of reliable transmission, therefore the problem of using special codes for channels with memory and construction of computationally effective decoding methods for correction of grouping errors is actual. For the class of random codes, an approach is known using information sets of limited diameter to correct error bursts. The size of the set of information sets grows linearly with increasing code length, and the construction of the set is described by a probabilistic procedure. This article considers the construction of a set of information sets for a special class of codes that correct error bursts called Gilbert codes. The sets of code positions of the smallest possible diameter are considered. Based on the calculation of the ranks of the submatrices of the parity-check matrix of the Gilbert code, the probability that the set of positions is an information set is estimated. For a given location of the information set, the positions of the corrected bursts are analyzed. Based on the analysis, a method for constructing a set of dense information sets for Gilbert codes for correcting all error bursts within the code correcting capacity is proposed. Using the features of setting the parameters of Gilbert codes, an estimate of the size of the resulting set of dense information sets is carried out. For a simple block size of the paritycheck matrix of a quasi-cyclic code, it is shown that for Gilbert codes a dense information set is located at any position. In the case of extended Gilbert codes, it is shown that sets of minimum diameter exist only at the last position of each block. A procedure for constructing a set of dense information sets of minimum diameter for Gilbert codes and their extensions is proposed. A comparison is made of the set size of information sets and the probability of obtaining it for Gilbert codes and random codes. It is shown that the number of information sets obtained by the proposed procedure does not increase with the length of the code. The results obtained in the paper demonstrate the possibility of developing computationally efficient decoders based on information sets when correcting single error bursts. Unlike random linear codes, for which the methods of constructing information sets including dense ones, are probabilistic, a procedure for guaranteed construction of a set of information sets of minimal diameter is specified for Gilbert codes. The quasi-cyclic structure of Gilbert codes allows constructing sets of dense information sets of smaller dimension than for random codes. The obtained results allow us to guarantee the correction of error bursts within the correcting capacity of Gilbert codes and their extensions with low computational complexity. The use of computationally efficient procedures for encoding and decoding error bursts will improve the reliability of message delivery in channels with memory.
This article discusses the question of assessing the probability of finding information sets in block-permutation and block-circulant matrices. Traditionally, interference-resistant coding is considered independent errors, however, in real systems they can be grouped and generate a so-called error burst. Known estimates of the probability of finding information sets are conducted for random matrices, and for correcting error bursts widespread block-permutation low density parity check codes (LDPC-codes) or block-circulant quasi cyclic codes (QC-codes) can be used. To estimate the probability of finding information sets mathematical modeling was used. Experiments have been carried out to identify parameters for specific structures that give the greatest probability of finding information sets. The article presents the results reflecting certain features in the values of the probability of finding information sets for matrices of different types, given assumptions and hypotheses about the features. Dependence of the presence of an information set from the size and location of its search interval inside the block permutation matrix was identified. The results of this research may be used to reduce the complexity of decoding by information sets, which, when considering random matrices, is exponential.
The performance of iterative decoding of low density parity check (LDPC) codes over binary erasure channels can be completely characterized by the study of stopping sets. Therefore, the burst erasure correction capability of a given LDPC code can be readily quantified by searching for stopping sets within consecutive bit nodes. In this work we study the optimal permutation of the bit nodes that will result in the maximum possible burst erasure correction capability for a given LDPC code. Noting that this is essentially a combinatorial optimization problem that is highly likely to be NP-hard, we adopt a simulated annealing based approach for finding the optimal permutation. We present bounds based on stopping sets that limit the burst erasure correction capability. As part of our results, we provide interleavers that greatly improve the burst erasure correction capability of protograph quasi-cyclic LDPC codes used in the WiMax standard.