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IEEE Communications Letters

Hybrid Hard-Decision Iterative Decoding of Regular Low-Density Parity-Check Codes

Pirouz Zarrinkhat, Amir H. Banihashemi

Published Apr 1, 2004• 12 citations
Publisher

Abstract

Hybrid decoding means to combine different iterative decoding algorithms with the aim of improving error performance or decoding complexity. In this work, we introduce "time-invariant" hybrid (H/sub TI/) algorithms, and using density evolution show that for regular low-density parity-check (LDPC) codes and binary message-passing algorithms, H/sub TI/ algorithms perform remarkably better than their constituent algorithms. We also show that compared to "switch-type" hybrid (H/sub ST/) algorithms, such as Gallager's algorithm B, where a comparable improvement is obtained by switching between different iterative decoding algorithms, H/sub TI/ algorithms are far less sensitive to channel conditions and thus can be practically more attractive.

DOI
10.1109/lcomm.2004.827438

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Hybrid decoding means to combine different iterative decoding algorithms with the aim of improving error performance or decoding complexity. In this work, we introduce "time-invariant" hybrid (H/sub TI/) algorithms, and using density evolution show that for regular low-density parity-check (LDPC) codes and binary message-passing algorithms, H/sub TI/ algorithms perform remarkably better than their constituent algorithms. We also show that compared to "switch-type" hybrid (H/sub ST/) algorithms, such as Gallager's algorithm B, where a comparable improvement is obtained by switching between different iterative decoding algorithms, H/sub TI/ algorithms are far less sensitive to channel conditions and thus can be practically more attractive.
Hybrid decoding is to combine different iterative decoding algorithms with the aim of improving error performance or decoding complexity. In this work, we introduce "time-invariant" hybrid (HTI) algorithms, and show that for regular low-density parity-check codes and binary message-passing algorithms, HTIalgorithms perform remarkably better than their constituent algorithms. We also show that compared to "switch-type" hybrid algorithms, such as Gallager's algorithm B, where a comparable improvement is obtained by switching between different iterative decoding algorithms, HTIalgorithms are far less sensitive to channel conditions and thus can be practically more attractive.
Time-invariant hybrid (HscrTI) decoding of irregular low-density parity-check (LDPC) codes is studied. Focusing on HscrTIalgorithms with majority-based (MB) binary message-passing constituents, we use density evolution (DE) and finite-length simulation to analyze the performance and the convergence properties of these algorithms over (memoryless) binary symmetric channels. To apply DE, we generalize degree distributions to have the irregularity of both the code and the decoding algorithm embedded in them. A tight upper bound on the threshold of MB HscrTIalgorithms is derived, and it is proven that the asymptotic error probability for these algorithms tends to zero, at least exponentially, with the number of iterations. We devise optimal MB HscrTIalgorithms for irregular LDPC codes, and show that these algorithms outperform Gallager's algorithm A applied to optimized irregular LDPC codes. We also show that compared to switch-type algorithms, such as Gallager's algorithm B, where a comparable improvement is obtained by switching between different MB algorithms, MB HscrTIalgorithms are more robust and can better cope with unknown channel conditions, and thus can be practically more attractive.
Time-invariant hybrid (HTI) decoding of irregular low-density parity-check (LDPC) codes is studied. Focusing on HTIalgorithms with majority-based (MB) binary message-passing constituents, we use density evolution and finite-length simulation to analyze the performance and the convergence properties of these algorithms. Tight upper bounds on the threshold of MB HTIalgorithms are derived, and it is proven that the asymptotic error probability for these algorithms tends to zero at least exponentially with the number of iterations. We devise optimal MB HTIalgorithms for irregular LDPC codes, and show that these algorithms outperform Gallager's algorithm A applied to optimized irregular LDPC codes. We also show that compared to switch-type algorithms, such as Gallager's algorithm B, where a comparable improvement is obtained by switching between different MB algorithms, MB HTIalgorithms are more robust, and can better cope with unknown channel conditions, and thus can be practically more attractive
Recent advances in coding theory have uncovered the previously forgotten power of Low-Density Parity-Check (LDPC) codes. Their popularity can be related to their relatively simple iterative decoders and their potential to achieve high performance close to shannon limit. These make them an attractive candidate for error correcting application in communication systems. In this thesis, we focus our research on the iterative decoding algorithms for Low-Density Parity-Check codes and present an improved decoding algorithm. First, the graph structure of LDPC codes is studied and a graph-based search algorithm to find the shortest closed walk and shortest cycle for each node of the graph is proposed. Then, the Deterministic schedule is applied on nodes of the graph with the objective of preserving the optimality of the algorithms. Finally, Hybrid Switch-Type technique is applied on the improved algorithms to provide a desirable complexity/performance trade-off. Hybrid Technique and Deterministic schedule are combined for decoding regular and irregular LDPC codes. The performance and complexity of the decoder is studied for Sum-Product and Gallager A algorithms. The result is a flexible decoder for any available LDPC code and any combination of decoding algorithms based on the communication systems need. In this technique, we benefit the high performance of soft-decision algorithms and low complexity of hard-decision algorithms by changing the decoding rule after a few iterations. Hence, a desirable performance can be obtained with less average number of soft iterations. Moreover, all the nodes do not update messages in each iteration. As a result, the total number of computations is reduced considerably
This paper considers a modified iterative version of the two-stage hybrid algorithm for decoding low-density parity- check (LDPC) codes. The hybrid-decision scheme is a decoding scheme used that combines two iterative decoding algorithms for decoding LDPC codes. This scheme is suitable for many applications such as audio and video transmission that are sensitive to time. The hybrid-decision scheme mixes between the characteristics of the soft-decision decoding scheme and the hard- decision decoding scheme to reduce the computational complexity of the whole decoding algorithm. The modification proposed in this paper is applied to the implementation-efficient reliability ratio weighted bit-flipping (IERRWBF) algorithm which represents hard-decision scheme in the hybrid algorithm. This modification is capable of achieving better performance than that of the hybrid decoding algorithm with reducing the number of iterations required at each SNR and approaching more to the performance of the SPA. This reduction is more observable as the maximum number of iterations assigned for the algorithm increases or as the code length increases with improving the error performance as proved by simulation results.
This correspondence presents the switch strategies for switch-type hybrid hard decision decoding algorithms for regular low-density parity-check (LDPC) codes. After the piecewise analysis of extrinsic information transfer functions for Gallager decoding algorithm B (GB), the normalized switch scheme (NSS), for which the majority-based algorithms and GB are two examples, is proposed. Then, several other examples of NSSs are presented and their convergence properties are analyzed based on the extrinsic information transfer (EXIT) functions. In simulations, the proposed NSSs show meaningful performance improvements and less sensitivity to channel parameter underestimations compared with GB for small and moderate block length codes.