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Systems engineering and electronics

Improved layered decoding algorithm for LDPC codes based on integer operation

MA Hui-miao

Published Jan 1, 2013• 0 citations
OpenAlex

Abstract

Based on the investigation of the low-density parity-check(LDPC) codes' layered decoding algorithm in additive white Gaussian noise(AWGN) channel,an improved layered decoding algorithm based on integer operation is proposed for decoding LDPC codes.All the variables are indicated as integers in the proposed algorithm,so it is very convenient for implementation in hardware.At the same time,a modified factor is introduced to improve the layered decoding algorithm.With this modified factor,its decoding performance is improved greatly.Simulation results in AWGN channel show that the improved layered decoding algorithm can not only reduce the computation complexity and accelerate the convergence rate,but also have a lower error floor.

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Based on the investigation of the low-density parity-check(LDPC) codes' layered decoding algorithm in additive white Gaussian noise(AWGN) channel,an improved layered decoding algorithm based on integer operation is proposed for decoding LDPC codes.All the variables are indicated as integers in the proposed algorithm,so it is very convenient for implementation in hardware.At the same time,a modified factor is introduced to improve the layered decoding algorithm.With this modified factor,its decoding performance is improved greatly.Simulation results in AWGN channel show that the improved layered decoding algorithm can not only reduce the computation complexity and accelerate the convergence rate,but also have a lower error floor.
In this paper,several conventional decoding algorithms of LDPC(Low-Density Parity-Check) codes over Additive White Gaussian Noise(AWGN) channels are investigated,and an improved decoding algorithm based on integer operation is proposed. Compared to normalized min-sum algorithm,a modified factor to improve the decoding performance is designed according to the states of hard decision in each iteration. It is convenient for hardware implementation with integer operation.The simulation results show that the algorithm performs better than LLR BP decoding algorithm in 2.1 dB and decodes fast with low complexity.
The LDPC codes decoding algorithm over additive white gaussian noise(AWGN) channels was studied,and a min-sum algorithm based on integer operation was proposed for decoding LDPC codes.All the variables were fixed length integers in this algorithm,which was very convenient for hardware implementation.At the signal-to-noise ratios(SNR) above 3dB,its performance was equal to that of sum-product algorithm whose variables were high precision floating point numbers.Also,a coefficient was designed to modify the min-sum algorithm,whose decoding performance was improved greatly especially at low SNR.And another achievement had been found that this algorithm had a lower error floor at high SNR.
We consider the convergence problem of the conventional decoding scheme of Low-Density Parity-Check(LDPC) codes over Additive White Gaussian Noise(AWGN) channels.In this correspondence,we propose a fast convergence decoding scheme based on quantization,which is a comprehensive method of taking advantage of the Layered Belief Propagation(LBP) algorithm,the Offset Min-Sum(OMS) algorithm and the quantization method.Compared to the conventional quantized Min-Sum algorithm,the proposed scheme efficiently reduces the decoding complexity and significantly accelerates the decoding convergence with no additional performance loss.We show that with simulations.
An improved parallel decoding approach of sum-product algorithm for low-density parity-check codes(LDPC) was presented in order to solve the problem of divergence in decoding iteration with finite precision,.In addition,the reason for improving the convergence speed was discussed detailedly and the pipeline structure was provided.By eliminating the unexpected state in which operation data didn't satisfy input rules due to the finite precision effect thus could not be preceded correctly,the iteration convergence was improved efficiently and led to decoding with no error.Compared with the original parallel approach,this improvement don't involve too much control logic and computational complexity.Simulation shows that the proposed decoding approach over additive white Gaussian noise(AWGN) channel achieves good performance,especially at high code rate,it suffers negligible performance loss compared with the forward-backward approach while reducing the operation complexity effectively.
Under the condition of the Additive White Gaussian Noise(AWGN) channel,both the hard and soft decision decoding algorithms suitable for LDPC codes are simulated and comparatively analyzed based on analyzing the decoding algorithm for LDPC codes.The variable message correlation for Log-Likelihood-Ratio Belief-Propagation(LLR-BP) algorithm in soft decision algorithm is decreased by introducing a multiplicative correction factor.The simulation results show that the decoding error-correction performance of the modified LLR-BP algorithm is greatly improved with little increase of computing complexity.
In this paper, we propose the modified minsum decoding algorithm of LDPC(Low-Density Parity-Check) code in the simplified difference-domain on the basis of detailed analysis of LDPC decoding algorithm in difference-domain. The simulation indicates that the proposed decoding algorithm offers almost no performance degradation compared with the BP(Belief Propagation) decoding algorithm in log-domain and the decoding algorithm in difference-domain and offers better performance than minsum decoding algorithm in log-domain and greatly reduces the computation complexity in AWGN(Additive White Gaussian Noise) channel and under BPSK(Binary Phase Shift Keying) modulation.