Iterative Joint Design of Fixed-Rate Source Codes and Multiresolution Channel Codes
نویسندگان
چکیده
We propose an iterative design algorithm for jointly optimizing source and channel codes. The joint design combines channel-optimized vector quantization (COVQ) for the source code with rate-compatible punctured convolutional (RCPC) coding for the channel code. Our objective is to minimize the average end-to-end distortion. For a given channel SNR and transmission rate, our joint source and channel code design achieves an optimal allocation of bits between the source and channel coders. This optimal allocation can reduce distortion by up to 6 dB over suboptimal allocations for the source data set considered. We also compare the distortion of our joint iterative design with that of two suboptimal design techniques: COVQ optimized for a given channel code and RCPC channel coding optimized for a given vector quantizer. Our joint code design performs better in all cases, and we reduce distortion by up to 4 dB compared with the standard COVQ design. We conclude by relaxing the xed transmission rate constraint and jointly optimizing the transmission rate, source code, and channel code.
منابع مشابه
Iterative Joint Design of Source Codes and Multiresolution Channel Codes
We propose an iterative design algorithm for jointly optimizing source and channel codes. The joint design combines channel-optimized vector quantization (COVQ) for the source code with rate-compatible punctured convolutional (RCPC) coding for the channel code. Our objective is to minimize the average end-to-end distortion. For a given channel SNR and transmission rate, our joint source and cha...
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