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International Symposium on Turbo Codes and Iterative Information Processing

On the asymptotic iterative decoding performance of low-density parity-check codes

Kamil Sh. Zigangirov, Michael Lentmaier

Published Jan 1, 2000• 2 citations
OpenAlex

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A class of pseudo-random compound error-correcting codes, called generalized low-density (GLD) parity-check codes, has been proposed recently. As a generalization of Gallager's low-density parity-check (LDPC) codes, GLD codes are also asymptotically good in the sense of minimum distance criterion and can be effectively decoded based on iterative soft-input soft-output (SISO) decoding of individual constituent codes. The code performance and decoding complexity of GLD codes are heavily dependent on the employed SISO decoding algorithm. In this paper, we show that Max-Log-MAP is an attractive SISO decoding algorithm for GLD coding scheme, considering the trade-off between performance and complexity in the practical implementations. A normalized Max-Log-MAP is presented to improve the GLD code performance significantly compared with using conventional Max-Log-MAP. Moreover, we propose two techniques, decoding task scheduling and reduced search Max-Log-MAP, to effectively reduce the decoding complexity without any performance degradation.

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Trapping and Absorbing Set Enumerators for Protograph-Based Generalized Low-Density Parity-Check Code Ensembles

Emna Ben Yacoub

Generalized low-density parity-check (GLDPC) codes have outstanding performance outperforming the standard low-density parity-check (LDPC) codes. However, the performance of these codes under iterative decoding can be degraded because of the presence of trapping, absorbing and fully absorbing sets in the code Tanner graphs. The (elementary) trapping and (fully) absorbing sets of protograph-based GLDPC codes are studied. The finite-length and asymptotic distributions of (elementary) trapping and (fully) absorbing sets for protograph-based GLDPC code ensembles are derived and evaluated. The asymptotic distributions can be efficiently computed by solving a system of equations. The relative minimum Δ-trapping/(fully) absorbing set size can be directly computed by adding one equation to the system of equations. This is useful for the code design where we can restrict the search to ensembles for which the minimum Δ-trapping and (fully) absorbing set sizes grow linearly with the blocklength. The normalized logarithmic asymptotic distributions of (elementary) trapping and (fully) absorbing sets for an example GLDPC code ensemble are evaluated.

International Symposium on Problems of Redundancy in Information and Control Systems (REDUNDANCY)•Oct 24, 2023•1 citation
A class of pseudo-random compound error-correcting codes, called generalized low-density (GLD) parity-check codes, has been proposed recently. As a generalization of Gallager's low-density parity-check (LDPC) codes, GLD codes are also asymptotically good in the sense of minimum distance criterion and can be effectively decoded based on iterative soft-input soft-output (SISO) decoding of individual constituent codes. The code performance and decoding complexity of GLD codes are heavily dependent on the employed SISO decoding algorithm. In this paper, we show that Max-Log-MAP is an attractive SISO decoding algorithm for GLD coding scheme, considering the trade-off between performance and complexity in the practical implementations. A normalized Max-Log-MAP is presented to improve the GLD code performance significantly compared with using conventional Max-Log-MAP. Moreover, we propose two techniques, decoding task scheduling and reduced search Max-Log-MAP, to effectively reduce the decoding complexity without any performance degradation.
Generalized low-density parity-check (GLDPC) codes have outstanding performance outperforming the standard low-density parity-check (LDPC) codes. However, the performance of these codes under iterative decoding can be degraded because of the presence of trapping, absorbing and fully absorbing sets in the code Tanner graphs. The (elementary) trapping and (fully) absorbing sets of protograph-based GLDPC codes are studied. The finite-length and asymptotic distributions of (elementary) trapping and (fully) absorbing sets for protograph-based GLDPC code ensembles are derived and evaluated. The asymptotic distributions can be efficiently computed by solving a system of equations. The relative minimum Δ-trapping/(fully) absorbing set size can be directly computed by adding one equation to the system of equations. This is useful for the code design where we can restrict the search to ensembles for which the minimum Δ-trapping and (fully) absorbing set sizes grow linearly with the blocklength. The normalized logarithmic asymptotic distributions of (elementary) trapping and (fully) absorbing sets for an example GLDPC code ensemble are evaluated.