Zhong, Fei; Zhao, Yue; Zhang, Tian; Zhang, Xuemin; Guo, Shuxu LDPC decoding algorithm based on compressive sensing reconstruction for denoise. (Chinese. English summary) Zbl 1349.94161 J. Yunnan Univ., Nat. Sci. 37, No. 5, 680-686 (2015). Summary: According to noise problems before low density parity check(LDPC) decoding, we propose LDPC decoding algorithm 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 algorithms of reconstruction, SP algorithm can get better results. MSC: 94B35 Decoding Keywords:low density parity check code; compressive sensing; decoding; noise PDF BibTeX XML Cite \textit{F. Zhong} et al., J. Yunnan Univ., Nat. Sci. 37, No. 5, 680--686 (2015; Zbl 1349.94161) Full Text: DOI