1Vector Quantization for Finite-State Markov Channels and Application to Wireless Channels

Vector quantization for joint source-channel coding over the finite-state Markov channel is studied. In particular, optimal decoding of a vector quantized source in the absence of channel state information is considered. Based on hidden Markov modeling of the channel output, two decoding strategies are proposed. The first one is a soft-decoder which estimates the source reconstruction vectors directly from a sequence of channel output samples. The second one is a hard-decoder based on joint MAP estimation of channel symbols and channel states. An iterative procedure for designing joint source-channel optimized vector quantizers is also proposed. Finally, the design of vector quantizers for wireless channels using a finite-state model is examined. Experimental results are provided for a Gauss-Markov source and flat-fading wireless channels. I