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IEEE Communications Letters

Application of efficient Chase algorithm in decoding of generalized low-density parity-check codes

S. Hirst, B. Honary

Published Sep 1, 2002• 14 citations
Publisher

Abstract

We consider the iterative decoding of generalized low-density (GLD) parity-check codes where, rather than employ an optimal subcode decoder, a Chase (1972) algorithm decoder more commonly associated with "turbo product codes" is used. GLD codes are low-density graph codes in which the constraint nodes are other than single parity-checks. For extended Hamming-based GLD codes, we use bit error rates derived by simulation to demonstrate this new strategy to be successful at higher code rates. For long block lengths, good performance close to capacity is possible with decoding costs reduced further since the Chase decoder employed is an efficient implementation.

DOI
10.1109/lcomm.2002.803487

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We consider the iterative decoding of generalized low-density (GLD) parity-check codes where, rather than employ an optimal subcode decoder, a Chase (1972) algorithm decoder more commonly associated with "turbo product codes" is used. GLD codes are low-density graph codes in which the constraint nodes are other than single parity-checks. For extended Hamming-based GLD codes, we use bit error rates derived by simulation to demonstrate this new strategy to be successful at higher code rates. For long block lengths, good performance close to capacity is possible with decoding costs reduced further since the Chase decoder employed is an efficient implementation.
In this paper we investigate a generalization of Gallager's (1963) low-density (LD) parity-check codes, where as component codes single error correcting Hamming codes are used instead of single error detecting parity-check codes. It is proved that there exist such generalized low-density (GLD) codes for which the minimum distance is growing linearly with the block length, and a lower bound of the minimum distance is given. We also study iterative decoding of GLD codes for the communication over an additive white Gaussian noise channel. The performance in terms of the bit error rate, obtained by computer simulations, is presented for GLD codes of different lengths.
This paper presents a lowered complexity version of a reliability-based iterative decoding algorithm for Generalized Low Density Parity Check (GLDPC) codes with BCH constituent codes using Soft-Input Soft-Output (SISO) Chase-II algorithm. Applied to Gallager-based global LDPC code, it shows that the proposed algorithm, when employed on GLDPC with the multi-error correction BCH subcodes, reduces the complexity of the conventional Soft-Decision Decoding (SDD) with Chase algorithm at a cost of slight degradation in the error performance. The approach is built on eliminating the employment of the Chase SISO decoder at the Generalized Check Nodes (GCNs) where the expected number of errors is within the correction capability of the Hard-Decision Decoder (HDD). As a case study, the decoder is considered under AWGN channel and Simulation results are presented showing the complexity and performance of the conventional and proposed algorithms.
In this paper, we propose an improved graph-based Chase-MP algorithm for iterative decoding of generalized low-density (GLD) codes, and also present analysis of the iterative decoding by using the Gaussian approximation. The simulation results on the additive white Gaussian noise (AWGN) channel show that the proposed algorithm can achieve good performance. During the iterative decoding analysis, we get a dynamic mathematical model of the Gaussian mean on iterations. As an application of the model derived, we compute decoding thresholds for several extended Bose-Chaudhuri-Hocquengnem (eBCH)-component GLD codes
A generalised low-density parity-check code (GLDPC) is a low-density parity-check code in which the constraint nodes of the code's graph are replaced with component or subcodes other than single parity checks. Gallager's bit-flipping algorithm for LDPCs is generalised to the class of GLDPCs with Hamming subcodes. The proposed weighted bit-flip voting (WBFV) method is iterative and uses only the hard decision decoder of the Hamming subcodes. Decoding of Hamming-based GLDPCs using WBFV has been simulated on the binary symmetric channel. Simulation results are presented showing the variation in performance with voting rule, graph construction and block length. In terms of the dependence of coding gains and complexity on the GLDPC block length, the proposed method is found to display a good performance to decoding complexity trade-off. Performance is found to compete well with other more conventional hard decision decoding schemes.
A generalization of Gallager's low-density parity-check codes is introduced, where as component codes single-error correcting Hamming codes are used instead of single-error detecting parity-check codes. Low-density (LD) parity-check codes were first introduced by Gallager in 1963. These codes are, in combination with iterative decoding, very promising for achieving low error probabilities at a reasonable cost. Results of computer simulations for long LD codes show, that a performance close to the Shannon capacity limit can be achieved. In this work, we consider a generalized version of low-density parity-check codes, where the decoding procedure can be based on the decoding of Hamming component codes.
Due to the more complex constraints, generalized low-density parity-check (GLDPC) codes can achieve better error performance but require much higher decoding complexities compared with the standard LDPC codes. In this paper, single-parity-check product-codes (SPC-PCs) are considered as the constituent codes in the super check nodes of a GLDPC code. Moreover, turbo iterations are used in decoding the SPC-PCs. The error performance and the decoder complexity of the proposed GLDPC code are compared with other LDPC code and GLDPC code.