Source Quantization and Coding over Noisy Channel Analysis

Runfeng Wang, Dan Song (), Jinkai Ren, Lin Wang and Zhiping Xu
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Runfeng Wang: Navigation College, Jimei University, Xiamen 361021, China
Dan Song: Navigation College, Jimei University, Xiamen 361021, China
Jinkai Ren: Department of Information and Communication Engineering, Xiamen University, Xiamen 361005, China
Lin Wang: Department of Information and Communication Engineering, Xiamen University, Xiamen 361005, China
Zhiping Xu: School of Ocean Information Engineering, Jimei University, Xiamen 361021, China

Mathematics, 2024, vol. 12, issue 23, 1-20

Abstract: Recently, lossy source coding based on linear block code has been designed using the duality principle, i.e., the channel decoding algorithm is employed to realize the lossy source coding. However, the quantization structure has not been analyzed in this compression technique, and the codebook design does not match the source characteristics well. Hence, the compression performance is not so good. To overcome this problem, the codebook design is correlated with the quantization structure in this work. It is found that the lossy source coding based on the linear block code can be defined as lattice vector quantization (VQ), which provides a new analytical perspective for the coding methodology. Then, the VQ scheme is generalized with the noisy channel to evaluate the transmission robustness of the continuous source compression. Finally, the codebook of the VQ scheme is optimally designed by uniforming the radiuses of the quantization subspace to reduce the quantization distortion. The proposed codebook outperforms existing codes in terms of its proximity to the rate–distortion limit, while also exhibiting enhanced robustness against channel noise.

Keywords: source compression; coding; vector quantization; noisy channel (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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