Research On LDPC Decoding Algorithm With Low Bit-error-rate

The 5G mobile communication system uses the LDPC code as the core coding technology of the data channel.The system puts forward higher requirements on the bit error rate and the convergence speed of decoding algorithm.In this paper,LDPC decoding algorithms with fast convergence and low bit error rate are studied under reasonable complexity.The following research work is mainly completed:1.An adaptive hybrid weighted bit flip?SLMWBF?decoding algorithm is proposed.Firstly,SLMWBF selects the minimum amplitude sum and the corresponding variable node amplitude as the reliable ratio divided,from weighted bit flip?RRWBF?algorithm of the weighted bit flip?WBF?algorithm,which is correctted by weight coefficient at the same time.Next,SLMWBF adjusts dynamically the reliability of some variable nodes,from the modified WBF?MWBF?algorithm,moreover,importing line weight information.Finally,the two kinds of optimized algorithms are adaptively mixed and decoded.When solving the problem of the RRWBF algorithm decoding,the algorithm can't distinguish from two bits,which have same reliability ratio and different amplitude.When solving the problem of the MWBF algorithm decoding,the algorithm only pays attention to unreliability of the smallest variable node.The algorithm solves the common problem of flipping repeatedly same bit in decoding.Simulation result shows that the SLMWBF performs about 0.5⁰.85dB better,compared with the WBF,MWBF,IMWBF,and RRWBF algorithms at the bit error rate BER=10^-5.When compared with MMWBF,the SLMWBF performs about 0.3dB better.At SNR=5dB,SLMWBF achieves better performance on the mean iteration times of decoding,compared with WBF,MWBF,IMWBF,and RRWBF algorithms,reduced by 23 to 27 times,decrease about 61%to 67%.Besides,the algorithm reduced 3 times,decrease about 25%,compared with MMWBF.It shows that the SLMWBF algorithm can significantly reduce the bit error rate and improve the convergence speed of the decoding.2.An Improved layered minimum sum algorithm based on weakening information oscillation is proposed.The algorithm weighted average with variable node information and posterior probability information of two iterations by adding weighte coefficient.Solve the problem of high bit error rate caused by large oscillation of variable node external information value in two iterations.Simulation result shows that the number of external information oscillations of the improved algorithm reduced by 110,when weighting coefficients is 0.9.It shows that the improved algorithm obviously weakens the oscillation of the external information of variable nodes.At the bit error rate BER=10^-5,compared with the layered minimum sum algorithm,the minimum sum algorithm,IMS-WVN algorithm and LLR-BP algorithm,improved layered minimum sum algorithm performs about 0.5dB,0.6dB,0.2dB,0.1dB better.At SNR=2.5dB,compared with the layered minimum sum algorithm,the minimum sum algorithm and IMS-WVN algorithm,the average number of iterations of the improved algorithm reduced by 5 times,8 times,2times and only one more than LLR-BP algorithm.It shows that the improved layered minimum sum algorithm reduces the bit error rate and improves the convergence speed of the decoding.