Joint design of fixed-rate source codes and multiresolution channel codes

We propose three new design algorithms for jointly optimizing source and channel codes. The joint designs combine 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 designs achieve 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 and by up to 4 dB relative to standard COVQ for the source data set considered. We nd that all three code designs have roughly the same performance when their bit allocations are optimized. This result follows from the fact that at the optimal bit allocation the channel code removes most of the channel errors, in which case the three design techniques are roughly equivalent. We also compare the robustness of the three techniques to channel mismatch. We conclude the paper by relaxing the xed transmission rate constraint and jointly optimizing the transmission rate, source code, and channel code.