Soft Decision Vector Quantization for Noisy Channels

This paper discusses the optimization of a vector quantizer whose indices are transmitted over a noisy channel. Rather than using a received index to select an entry in the codebook (which implies a hard decision on the index), the decoder uses the received signal and the channel statistics to weight the codebook entries in order to produce a good reconstructed signal. The corresponding approach will be called Soft Decision Vector Quantization (SDVQ). It is shown that SDVQ achieves a significant performance improvement over both the source optimized VQ and the channel optimized VQ.