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IEEE Communications Letters

A PEG Construction of Finite-Length LDPC Codes with Low Error Floor

Sina Khazraie, Reza Asvadi, Amir H. Banihashemi

Published Jun 5, 2012• 43 citations
Publisher

Abstract

The progressive-edge-growth (PEG) algorithm of Hu et al. is modified to improve the error floor performance of the constructed low-density parity-check (LDPC) codes. To improve the error floor, the original PEG algorithm is equipped with an efficient algorithm to find the dominant elementary trapping sets (ETS's) that are added to the Tanner graph of the under-construction code by the addition of each variable node and its adjacent edges. The aim is to select the edges, among the candidates available at each step of the original PEG algorithm, that prevent the creation of dominant ETS's. The proposed method is applicable to both regular and irregular variable node degree distributions. Simulation results are presented to demonstrate the superior ETS distribution and error floor performance of the constructed codes compared to similar codes constructed by the original and other modifications of the PEG algorithm.

DOI
10.1109/lcomm.2012.060112.120844

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The progressive-edge-growth (PEG) algorithm of Hu et al. is modified to improve the error floor performance of the constructed low-density parity-check (LDPC) codes. To improve the error floor, the original PEG algorithm is equipped with an efficient algorithm to find the dominant elementary trapping sets (ETS's) that are added to the Tanner graph of the under-construction code by the addition of each variable node and its adjacent edges. The aim is to select the edges, among the candidates available at each step of the original PEG algorithm, that prevent the creation of dominant ETS's. The proposed method is applicable to both regular and irregular variable node degree distributions. Simulation results are presented to demonstrate the superior ETS distribution and error floor performance of the constructed codes compared to similar codes constructed by the original and other modifications of the PEG algorithm.
The progressive-edge-growth (PEG) algorithm for constructing Tanner graphs with large girth by progressively establishing edges/connections between symbol nodes and check nodes in an edge-by-edge way is highly known to construct low-density parity-check (LDPC) codes at short block lengths for achieving good performance. This paper proposed an improved PEG construction for irregular codes, which heuristically selects good codes from random graphs for short block lengths. The simulation results are given to demonstrate that the proposed algorithm gians better BER performance for high signal-to-noise (SNR) ratios without performance loss for low-SNR region, i.e. low error floor.
There exist many different algorithms to construct good low-density parity-check (LDPC) codes. To maximize the girth of the bipartite graph, which represents the LDPC code, the progressive edge-growth (PEG) algorithm was introduced. This construction methods leads for irregular LDPC codes to a lower error floor, but also to a performance loss in the waterfall region compared with randomly constructed LDPC codes. In this paper, we describe a modification of the PEG algorithm that improves the performance in the waterfall region. Furthermore, this modified PEG algorithm yields codes with lower error floors and a slightly better performance in the waterfall region than randomly constructed LDPC codes
The Progressive edge-growth (PEG) algorithm was proven to be a simple and effective approach in designing Low-density parity-check (LDPC) codes. However, the Tanner graph constructed with the PEG algorithm is non-structured, which leads to random distributions of the positions of 1's in the corresponding parity-check matrix. In this paper, an improved algorithm based on the PEG algorithm for constructing quasi-cyclic (QC) LDPC codes is proposed. The proposed algorithm can eliminate short cycles efficiently and gain low error-floors. What is more important, the proposed QC-LDPC codes construction method is hardware-friendly because of its quasi-cyclic structure. Our simulation results demonstrate that the codes constructed with the proposed algorithm has better performance than the PEG algorithm over the additive white Gaussian noise (AWGN) channel and Rayleigh flat fading channel.
We propose a simple modification to the progressive edge-growth (PEG) algorithm in order to control the girth of low-density parity-check (LDPC) code Tanner graphs constructed. Using the modified algorithm, the edge densities in short irregular rate-% LDPC code graphs can be increased without increasing the correlation between edges in graphs by creating cycles of undesired length. Density evolution (DE) optimized symbol node degree distributions used for constructing short-to-medium length codes were further optimized (slightly altered) while maintaining the maximum edge correlation (minimum local girths) that exists in graphs constructed using the unaltered DE optimized distributions. As a result of improved degree sequences (and graph densities) which were derived, short-to-medium length LDPC codes with lower error floors than published for LDPC codes of identical length and rate were found. These slightly denser codes have lower error floor than codes constructed using DE optimized degree distributions in PEG algorithms modified for improved approximate cycle extrinsic message degrees (ACE). Simulation results show that, at a code length of 512, efficient irregular rate-% PEG codes have significantly lower error floors than a rate-% IEEE 802.16e (WiMAX) LDPC code of length 576.
Trapping sets (TSs) are known to cause error floors in regular and irregular low-density parity-check (LDPC) codes. By avoiding major error-contributing TSs during the code construction process, codes with low error floors can effectively be built. In it has been shown that TSs labeled as [w;u] are considered as being equivalent under the automorphism of the graph and are therefore contributing equally to the error floor. However, TSs with the same label [w;u] are not identical in general, particularly for the case of irregular LDPC codes. In this paper, we introduce a parameter e that can identify the number of "distinguishable" cycles in the connected subgraph induced by an elementary trapping set. Further, we propose a code construction algorithm, namely the Progressive-Edge-Growth Approximate-minimum-Cycle-Set-Extrinsic-message-degree (PEG-ACSE) method, that aims to avoid small elementary trapping sets (ETSs), particularly detrimental ETSs. We also develop theorems evaluating the minimum possible ETSs formed by PEG construction algorithms in general. We compare the characteristics of the codes built using the proposed method and those built using PEG-only or PEG-Approximate-minimum-Cycle-Extrinsic-message-degree (PEG-ACE) methods. Results from simulations show that the codes constructed using the proposed PEG-ACSE method produce lower error rates, particularly at the high signal-to-noise (SNR) region, compared with codes constructed using other PEG-based algorithms.
The progressive edge-growth (PEG) algorithm is known to construct low-density parity-check (LDPC) codes at finite code lengths with large girths by establishing edges between symbol and check nodes in an edge-by-edge manner. The linear-encoding PEG (LPEG) algorithm, a simple variation of the PEG algorithm, can be applied to generate linear time encodable LDPC codes whose m parity bits p1, p2, ..., p m are computed recursively in m steps. In this article, we propose modifications of the LPEG algorithm to construct LDPC codes whose number of encoding steps is independent of the code length. The maximum degree of the symbol nodes in the Tanner graph is denoted by ; The m parity bits of the proposed LDPC codes are divided into subgroups and can be computed in only steps. Since , the number of encoding steps can be significantly reduced. It has also been proved that the PEG codes and the codes proposed in this article have similar lower bound on girth. Simulation results showed that the proposed codes perform very well over the AWGN channel with an iterative decoding.