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IEEE Transactions on Information Theory

A new series of concatenated codes subject to matrix type-Bcodes

D. C. Voukalis

Published May 1, 1982• 16 citations
Publisher

Abstract

Some important aspects of a series of concatenated codes subjected to matrix type-Bcodes are investigated. Concatenated matrix codes and the concatenated quadratic residue codes especially are emphasized. An analysis of the error patterns, which can be corrected with the matrix coding, also is given. These codes are suitable for compound channels with memory (i.e., channels on which burst, cluster, and random errors occur). Explicit formulas are given for the number of bursts, cluster, and random errors that can be corrected with these codes. Decoding schemes and techniques for studying error propagation in the proposed codes are given. In particular a new decoding algorithm for a concatenated matrix code is given. The performance of coding and decoding schemes of the various types of concatenated codes can be tested in practice.

DOI
10.1109/tit.1982.1056500

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Some important aspects of a series of concatenated codes subjected to matrix type-Bcodes are investigated. Concatenated matrix codes and the concatenated quadratic residue codes especially are emphasized. An analysis of the error patterns, which can be corrected with the matrix coding, also is given. These codes are suitable for compound channels with memory (i.e., channels on which burst, cluster, and random errors occur). Explicit formulas are given for the number of bursts, cluster, and random errors that can be corrected with these codes. Decoding schemes and techniques for studying error propagation in the proposed codes are given. In particular a new decoding algorithm for a concatenated matrix code is given. The performance of coding and decoding schemes of the various types of concatenated codes can be tested in practice.
The polynomial of correctable patterns is defined In [l] as the weight enumerator of the set of error patterns correctable by a given decoding algorithm. The polynomials of uncorrectable and miscorrected patterns can be defined as well ([5] aid (61) These polynomials allow a compact representation of a decodiilg alient to compute the coriection probabillty and ability thiougli a memoryless symetric channel. Our purpose heie is to compute the polynomials of correctable patThese results are geneialised in [5] and [SI for erasure channels. terns of concatenated codes for dlffeient decoding algorithms. I) We give the weight distribution of the erior patterns correctable by the standard decoding algorithm. * We give bounds for the weight distribution of the error patterns correct able by Block- Zyablov algorithm. This new method for evaluating concatenated codes will thus provide to evaluate the standard algorithm. It will also give a with precision the performances of the Block-Zyablov decoding algorithm which needed, up to llow, a (much more expensive) simulation. ill compute the decoding performances of the rdstrom-Robinson ([4, p. 731) inlier code, and a Reed-Solomon (255,223,33) outer code over F2~6.
Iterative algorithms for decoding over erasure-burst channels have attracted much interest lately due to their simplicity. Although the performance of these techniques is typically good, it may not be optimal if the underlying matrix used for decoding is not properly chosen. In this paper, we construct matrices that lead to optimal performance when used with iterative decoding over erasure-burst channels. We also develop a simple decoding technique that makes use of these same matrices to decode any linear code over error-burst channels. For cyclic codes, this algorithm is optimal.
Concatenated codes are effectively used in different approaches of error-correcting theory. We suggest new concatenated code construction that is composed of outer LDPC code and a particular designed inner LDPC code. Special optimization procedure was developed to obtain inner code with specific error-correcting characteristics. We apply the decoder of woven codes to this construction, while reducing the complexity of decoding procedure compared to a classic decoder of LDPC code. Furthermore, we improve the performance of our scheme with puncturing the code symbols. The resulting concatenated construction outperforms low-rate LDPC from the 5G standard. Besides this, we demonstrate the performance of code with a special parity-check matrix consisting of parity-check matrices of inner and outer codes from our suggested construction.
In this chapter, we continue the discussion on concatenated codes, which was initiated in Section 5.4. The main message to be conveyed in this chapter is that by using concatenation, one can obtain codes with favorable asymptotic performance—in a sense to be quantified more precisely—while the complexity of constructing these codes and decoding them grows polynomially with the code length. We first present a decoding algorithm for concatenated codes, due to Forney. This algorithm, referred to as a generalized minimum distance (in short, GMD) decoder, corrects any error pattern whose Hamming weight is less than half the product of the minimum distances of the inner and outer codes (we recall that this product is a lower bound on the minimum distance of the respective concatenated code). A GMD decoder consists of a nearest-codeword decoder for the inner code, and a combined error–erasure decoder for the outer code. It then enumerates over a threshold value, marking the output of the inner decoder as erasure if that decoder returns an inner codeword whose Hamming distance from the respective received sub-word equals or exceeds that threshold. We show that under our assumption on the overall Hamming weight of the error word, there is at least one threshold for which the outer decoder recovers the correct codeword. If the outer code is taken as a GRS code, then a GMD decoder has an implementation with time complexity that is at most quadratic in the length of the concatenated code.
The polynomial of correctable patterns is defined in [1] as the weight enumerator of the set of error patterns correctable by a given decoding algorithm. The polynomials of uncorrectable and miscorrected patterns can redefined as well ([5] and [6]). These polynomials allow a compact representation of a decoding algorithm which is sufficient to compute the correction probability and the miscorrection probability through a memoryless symetric channel. These results are generalized in [5] and [6] for erasure channels. Our purpose here is to compute the polynomials of correctable patterns of concatenated codes for different decoding algorithms. We give the weight distribution of the error patterns correctable by the standard decoding algorithm. We give bounds for the weight distribution of the error patterns correctable by Block- Zyablov algorithm. This new method for evaluating concatenated codes will thus provide an efficient way to evaluate the standard algorithm. It will also give a way to evaluate with precision the performances of the Block- Zyablov decoding algorithm which needed, up to now, a (much more expensive) simulation. As an example, we will compute the decoding performances of the concatenation of the Nordstrom-Robinson ([4, p. 73]) inner code, and a Reed-Solomon (255,223,33) outer code over F/sub 256/.
This paper presents two types of concatenated finite-geometry and finite-field LDPC codes which have the distinct features of both finite geometry and finite field LDPC codes, such as large minimum distances, no small trapping sets, fast decoding convergence, capable of correcting both random errors and bursts of erasures, flexibility in code construction, cyclic and quasi-cyclic structures. It is shown that these concatenated codes are globally coupled LDPC codes and they perform well over the AWGN and binary erasure channels with a two-phase iterative decoding scheme.