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International Conference on Wireless Communications, Networking and Mobile Computing

EXIT Trajectories of Irregular LDPC Codes

Zheng He, Huaying Zhou, Jiongyi Yi

Published Sep 1, 2009• 0 citations
Publisher

Abstract

In this paper, we propose the concept of extrinsic information transfer (EXIT) trajectories, and show how to use it to analyze convergence performance of belief propagation (BP) decoding for irregular low-density parity-check (LDPC) codes. The proposed analysis method utilizes the EXIT characteristics in an improved way, and allows us to calculate the convergence threshold quickly and accurately. On the binary phase-shift keying (BPSK) modulated additive white Gaussian noise (AWGN) channel, the achieved threshold values for the enumerated irregular LDPC codes have error to those computed by density evolution only about 0.03 dB.

DOI
10.1109/wicom.2009.5302599

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In this paper, we propose the concept of extrinsic information transfer (EXIT) trajectories, and show how to use it to analyze convergence performance of belief propagation (BP) decoding for irregular low-density parity-check (LDPC) codes. The proposed analysis method utilizes the EXIT characteristics in an improved way, and allows us to calculate the convergence threshold quickly and accurately. On the binary phase-shift keying (BPSK) modulated additive white Gaussian noise (AWGN) channel, the achieved threshold values for the enumerated irregular LDPC codes have error to those computed by density evolution only about 0.03 dB.
Low density parity check (LDPC) codes are known to achieve a performance very close to the Shannon capacity limit on Additive White Gaussian Noise (AWGN) and erasure channels. The extrinsic information transfer (EXIT) chart is a powerful method for analyzing iteratively decoded codes such as Turbo codes. EXIT charts were introduced as a method for representing how the mutual information between the decoder output and the transmitted bits changes over turbo decoding iterations. It is possible to apply the EXIT chart method to LDPC codes by treating the LDPC decoder as a concatenation of variable and check nodes. However the achieved convergence threshold values obtained with the EXIT charts are (plusmn0.1) dB away from the more precise results derived from the density evolution (DE) method. Subsequently, the EXIT trajectories method was proposed as an improved performance-analysis method for LDPC codes under belief propagation (BP) decoding and achieved more accurate convergence threshold values than the EXIT chart method. In this paper, the EXIT chart and the EXIT trajectories methods are proposed as analysis tools to compare between the BP, log likelihood and max log likelihood decoding algorithms for LDPC codes in terms of convergence thresholds. Furthermore, a comparison between EXIT chart, EXIT trajectories and DE methods is introduced for the mentioned LDPC codes. Simulations and numerical calculations on convergence thresholds for various ensembles of (dv, dc) regular LDPC codes for binary input AWGN channels are performed which results that the BP is the best decoding algorithm for LDPC code followed by the log likelihood and the max log likelihood algorithms, respectively. Also, the EXIT trajectory method yields more accurate results than EXIT charts which come very close to the DE method, while being more convenient numerically as a code research tool than the latter which require many Fourier transform operations.
The extrinsic information transfer (EXIT) charts are used to analyze the sum-product decoding algorithm of low-density parity-check (LDPC) codes. The codes are optimized by performing curve fitting on EXIT charts. This technique is developed for binary erasure channels based on area property and is extended to other channels. We show that on channels where the area property is not valid, the curve fitting approach is a sub-optimal method of optimizing for the best convergence threshold. On Gaussian channels, the messages from variable nodes to check nodes are approximated by a symmetric Gaussian distribution. We prove that the check node detector mutual information transfer function derived using this approximation is an upper bound. So the EXIT chart analysis predicts an optimistic value for the convergence threshold. We give an empirical lower bound for the check node detector mutual information transfer function. For few irregular LDPC codes designed for AWGN channel using density evolution, we have examined the accuracy of convergence thresholds predicted by EXIT charts using these bounds for the check node transfer function. The analysis of EXIT chart technique presented in this paper can be extended to other channels for which the distribution of channel messages can be approximated by a symmetric Gaussian/Gaussian mixture distribution.
We exploit extrinsic information transfer functions of single parity-check and repetition codes over the binary input additive white Gaussian noise (biAWGN) channel, derived by the authors, for asymptotic performance analysis of belief propagation decoding of low-density parity-check codes. The approach is based on a Gaussian approximation (GA) of the density evolution algorithm using the mutual information measure. We show that this method allows more accurate prediction of the decoding threshold in the biAWGN channel than the earlier known GA methods
This paper investigates about the usefulness of some recently published low complexity upper bounds on belief-propagation decoding thresholds for irregular low-density parity-check (LDPC) codes to analyze their performance on memoryless binary input - additive white Gaussian noise (BI-AWGN) channels, with sum-product decoding. Irregular LDPC codes are known to perform better than regular ones, and to exhibit, like them, the so called “threshold phenomenon”, being the threshold defined as the maximum noise level such that an arbitrarily small bit-error probability can be achieved as the block length tends to infinity. We use a simplified analysis of the belief-propagation decoding algorithm, i.e., consider a Gaussian approximation for message densities under density evolution, and a simple algorithmic method, defined recently, to estimate the decoding thresholds for regular and irregular LDPC codes on BI-AWGN channels.
In this paper we investigate the asymptotic behavior of belief propagation algorithm for low density parity check (LDPC) codes over additive white Gaussian noise (AWGN) channel when there is an incorrect estimate of the channel noise power. We propose a computationally efficient method to compute the convergence threshold values for both regular and irregular codes and show that these values are consistent with simulation results for the codes with finite block lengths. The effect of imperfect channel estimation on EXIT charts of variable nodes and check nodes is also investigated.
We exploit extrinsic information tranfer functions of single parity-check and prepetition codes over the binay input additive white Gaussian noise (biAWGN) channel, for asymptotic performance analysis of belief propagation decoding of low-density parity-check codes. The approach is based on a Gaussian approximation (GA) of the density evolution algorithm using the mutual information measure. We show that our method allows more accurate prediction of the decoding threshold in the biAWGN channel than the earlier known GA methods.