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Journal of Circuits and Systems

Iterative decoding algorithm with channel adaptation for LDPC codes

Guojun Han, Xingcheng Liu

Published Jan 1, 2010• 0 citations
OpenAlex

Abstract

For short to moderate block-length LDPC codes, a large number of uncorrected error frames causes the increase of average number of iterations in the region of low SNR(Signal-to-Noise Ratio) and the oscillation of some variable nodes degrades the error performance in the region of medium to high SNR. In order to reduce the average number of iterations in the region of low SNR and improve error performance in the region of medium to high SNR, an iterative decoding algorithm with channel adaptation is proposed. The decoding method with pre-decision making based on error patterns of check-sum and weighted average message is adopted in this algorithm. Through the primary role of early decision method on reducing average iterations at low SNR and weighted average message on reducing error frames at medium to high SNR, iterative decoding with channel adaptation is realized and high efficient decoding is achieved. Simulation results show that, with the proposed algorithm, the average number of iterations is reduced in the region of low SNR without noticeable error performance degradation, and the error performance is improved in the region of medium to high SNR without obvious increase of the number of iterations compared with standard BP algorithm.

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For short to moderate block-length LDPC codes, a large number of uncorrected error frames causes the increase of average number of iterations in the region of low SNR(Signal-to-Noise Ratio) and the oscillation of some variable nodes degrades the error performance in the region of medium to high SNR. In order to reduce the average number of iterations in the region of low SNR and improve error performance in the region of medium to high SNR, an iterative decoding algorithm with channel adaptation is proposed. The decoding method with pre-decision making based on error patterns of check-sum and weighted average message is adopted in this algorithm. Through the primary role of early decision method on reducing average iterations at low SNR and weighted average message on reducing error frames at medium to high SNR, iterative decoding with channel adaptation is realized and high efficient decoding is achieved. Simulation results show that, with the proposed algorithm, the average number of iterations is reduced in the region of low SNR without noticeable error performance degradation, and the error performance is improved in the region of medium to high SNR without obvious increase of the number of iterations compared with standard BP algorithm.
To reduce the average number of decoding iterations in the region of low SNR(signal to noise ratio) and weaken the oscillation of the LLR(logarithm likelihood ratio),discovered the variation law of the check nodes'LLR and the checksum,in the error frame of the short and middle length LDPC codes.Based on the law,proposed an improved BP algorithm of LDPC decoding.In the algorithm,developed an early stopping criterion to reduce the average number of decoding iterations in the region of low SNR.And to improve the decoding performance by weakening the oscillation of the LLR,modified the update algorithm of check node.Simulation results show that,the algorithm reduces the number of iteration while the performance is not reduced in the region of low SNR,the decoding performance is improved while the number of iteration is not changed in the region of middle and high SNR.
The paper presents a novel approach to reduce the bit error rate (BER) in iterative belief propagation (BP) decoding of low density parity check (LDPC) codes. The behavior of the BP algorithm is first investigated as a function of number of decoder iterations, and it is shown that typical uncorrected error patterns can be classified into 3 categories: oscillating, nearly-constant, or random-like, with a predominance of oscillating patterns at high Signal-to-Noise (SNR) values. A proposed decoder modification is then introduced based on tracking the number of failed parity check equations in the intermediate decoding iterations, rather than relying on the final decoder output (after reaching the maximum number of iterations). Simulation results with a rate ¿ (1024,512) progressive edge-growth (PEG) LDPC code show that the proposed modification can decrease the BER by as much as 10-to-40%, particularly for high SNR values.
A weighted belief propagation decoding algorithm for low-density parity-check decoding is proposed to accelerate the convergence of decoding and reduce the number of decoding iterations. We propose an early stopping criterion which is based on the average weighted reliability measure of the hard output of decoder to detect undecodable blocks in an early stage of the decoding process. In addition, an adaptive weighted iteration scheme is proposed to increase the convergence speed of belief propagation (BP) decoding and therefore improve the error performance. The evolution of the adaptive weighting factor with the number of decoding iterations is based on the relative entropy between two consecutive ”a posteriori” probabilities distribution at decoder output. Simulation results show that the proposed algorithm can achieve about 0.2-0.4 dB coding gain improvement on average while reducing up to about 50%-85% iterations for decoding at low to medium E(subscript b)/ N(subscript 0) , compared with the conventional BP based algorithms.
According to no-convergence of falsely oscillating iteration in the low-density parity-check(LDPC) decoding at the range from medium to high SNRs(Signal to Noise Ratios),we propose a modified LDPC belief propagation(BP) decoding algorithm,i.e.soft value zero-forcing BP algorithm.By setting extrinsic information of the oscillating iteration bit nodes into zero,the impact on the iteratively decoding from false channel information is greatly reduced.And it also improves the performance of the decoding algorithm.Furthermore,a decision criterion of oscillating iteration nodes is presented to increase the accuracy of the decision.Simulation results show that the proposed algorithm has better decoding performance than that of the BP algorithm with the same iterations at medium and high SNRs.
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.