基于压缩感知重建去噪后的LDPC译码算法

针对LDPC译码前的噪声问题,提出一种基于压缩感知重建去噪后的LDPC译码算法.首先,在接收端使用CS算法对系统的接收信号进行观测,恢复,消除信道传输过程中的噪声信息;然后,将恢复信号直接作为接收信号送入LDPC的译码器.仿真计算证明,这种改进的算法能有效减少噪声影响,降低LDPC的误码率,提高系统译码性能,在码长为512时,误码率可降低到10-5,并且受稀疏度,传输速率和CS重构算法影响.对比4种CS重构的贪婪算法,SP算法得到的效果较好.

LDPC decoding algorithm based on compressive sensing reconstruction for denoise

According to noise problems before LDPC decoding,we propose LDPC decoding algorithm,which based on compressive sensing reconstruction for denoise.First of all,at the receiving end,we use CS algorithm observing and recovering the received signal of system,to eliminate the noise in the process of information channel transmission,and then we use the restoring signal as a received signal directly into the LDPC decoder.The simulation calculation shows that the improved algorithm can effectively reduce the effects of noise,reduce the LDPC error rate and improve the decoding performance of the system,when the code length is 512,the error rate can be reduced to 10-5.And the error rate is influenced by the sparsity,the transmission rate and CS reconstruction algorithm.Comparing to four kinds of CS greedy algorithm reconstruction,SP algorithms get better.