The joint source channel coding (JSCC) system is sensitive to the changing channel characteristics, because the optimally designed source-channel codepair always needs to be redesigned when the transmission environme...
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The joint source channel coding (JSCC) system is sensitive to the changing channel characteristics, because the optimally designed source-channel codepair always needs to be redesigned when the transmission environment is updated. A solution is to seek a commoncodepair for variable channels. Channel model 3 (CM3) is a variable on-body channel following the Weibull distribution, which is analyzed in four conditions due to varying shape factors, namely with exponential, Rayleigh, log-normal and normal distributions. The JSCC system is considered in this paper based on double protograph low-density parity-check (dp-ldpc) codepair over the variable CM3 channel. Firstly, four dp-ldpccodepairs are searched by the conventional differential evolution (DE) algorithm with four distributions of the Weibull model, respectively. However, these four codepairs only present good bit-error ratio performance in their own distribution, and have error floors in the other three. To resolve the problem, an artificial intelligence method based on principle component analysis (PCA) algorithm is designed to extract the commoncodepair. It is demonstrated that the commoncodepair performs well in noise-varying and practical-parameter transmissions. Instead of four DE codepairs, the designed one PCA codepair provides a strong technical support to low-complexity manufacturing such as eHealthcare.
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