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Electronic Design Engineering

Research of LDPC decoding based on LLR BP algorithm

Yin Shuang-shuang

Published Jan 1, 2012• 0 citations
OpenAlex

Abstract

In iterations processing of LLR BP algorithm for LDPC decoding,the computational of check nodes renewal is high;The decoding performance will be reduced,while there are lots of loops in short LDPC codes.According to these problems,a new LLR BP decoding algorithm based on Hybrid Check-Variable offset processing is proposed in this paper.Decrease complexity by adjusting amplitudes of check nodes processing and relativity of variable nodes by adjusting their information.Simulation results show that this improved decoding algorithm,compared with LLR BP algorithm,is consideration to decoding performance of LDPC and computational complexity.

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In iterations processing of LLR BP algorithm for LDPC decoding,the computational of check nodes renewal is high;The decoding performance will be reduced,while there are lots of loops in short LDPC codes.According to these problems,a new LLR BP decoding algorithm based on Hybrid Check-Variable offset processing is proposed in this paper.Decrease complexity by adjusting amplitudes of check nodes processing and relativity of variable nodes by adjusting their information.Simulation results show that this improved decoding algorithm,compared with LLR BP algorithm,is consideration to decoding performance of LDPC and computational complexity.
In iterations processing of LLR BP algorithm for LDPC decoding, the computational complexity of check nodes renewal is high; The decoding performance will be reduced, while there are lots of loops in short LDPC codes. According to these problems, a new LLR BP decoding algorithm based on Hybrid Check-Variable offset processing is proposed in this paper. Decrease complexity by adjusting amplitudes of check nodes processing and relativity of variable nodes by adjusting their information. Simulation results show that this improved decoding algorithm, compared with LLR BP algorithm, is consideration to decoding performance of LDPC and computational complexity.
The Tanner graph of long LDPC codes usually has no loops and LLR BP algorithm is the best soft-decision decoding algorithm.But the Tanner graph of short LDPC codes usually has loops,so information within variable nodes doesn't satisfy the condition of independent identical distribution and the decoding performance of LLR BP algorithm will decrease.In this paper,a modified LLR BP algorithm is proposed,which can reduce the relativity of information within variable nodes by adjusting the iterative process of variable nodes information.Simulation results show that the LDPC decoding performance of the modified LLR BP algorithm is more effective than that of LLR BP algorithm,Normalized BP algorithm and offset BP algorithm.
To improve the decoding speed and reduce the complexity of low-density parity-check (LDPC) codes, this paper proposes a hybrid LDPC decoding algorithm that combined with the distribution characteristics of log-likelihood ratio (LLR) of all variable node information before each iteration. During the process of decoding, there is a judgment based on an interval value and a threshold value to select the Belief Propagation (BP) algorithm or the Minimal Sum (MS) algorithm to decode, so the proposed hybrid algorithm effectively combines the excellent performance of BP algorithm and the simple operation of MS algorithm. The simulation results show that the algorithm can greatly reduce the computational complexity and achieve similar decoding performance compared with the 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.
In order to reduce the performance loss of UMP BP-based decoding algorithm relative to LLR-BP decoding algorithm,an improved UMP BP-based decoding algorithm is proposed.When the check nodes process the message,the normalized BP-based decoding algorithm and offset BP-based decoding algorithm are integrated effectively by setting a correction factor and an offset factor reasonably.When the variable nodes process the message,an oscillation compensation algorithm based on LLR-BP decoding algorithm is introduced.Simulation results show that based on the irregular LDPC codes and under the condition of the same bit error rate within a certain range,the improved UMP BP-based decoding algorithm improves the decoding performance greatly compared with the three decoding algorithms which are based on UMP BP,normalized BP and offset BP decoding algorithms,respectively,and therefore quite efficiently approaches to the LLR-BP decoding algorithm which has excellent performance.
At present, Low-Density Parity-Check (LDPC) codes widely used in many fields of communications have the best performance of all the Error Correcting Codes (ECC). This paper mainly studies the decoding algorithms of LDPC. It proposes an improved algorithm which is named Check-Variable nodes Hybrid(CVH) algorithm on the basis of the existing algorithms. The CVH algorithm can reduce the computational complexity during the check-node update while overcome with the correlation between the variable-node news in a code with circles. As well as, comparing with the original algorithms the performance of the new one saves 0.1 and 0.3 dB than Log-likelihood Ratios (LLR) Belief Propagation (BP) and BP - based algorithms under Additive White Gaussian Noise (AWGN) channel when the Bit Error Rate (BER) falls to through the simulation. This point shows that this algorithm can increase the decoding performance and reduce the error rate effectively.