Joint Channel Coding based on LDPC Codes with Gaussian Kernel Reflecton and CS Redundancy
Fei Zhong, Shuxu Guo, Xu Xu · Applied Mathematics & Information Sciences · 2013
Abstract: This paper proposes a new joint decoding algorithm frame based on compressed sensing CS and LDPC (Low-Density Parity-Check) codes. Redundant information can be effectively extracted and amplified by CS reconstruction as a compensation to correct decoding of LDPC codes. We adopt Gaussian kernel function of image segmentation as a reflection. Simulation results indicate, compared with LDPC algorithm, the algorithm presented in this paper can obviously make BER (bit error ratio) lower and improve system decoding performance, and different variance of Gaussian kernel function can obtain different results.