Channel optimized vector quantization based on Maximum a Posteriori hard decision demodulation

We design a maximum a posteriori hard-decision demodulated channel optimized vector quantizer (COVQ) that exploits the non-uniformity of the quantized source. We consider memoryless Gaussian and Gauss-Markov sources transmitted over a binary phase-shift keying modulated additive white Gaussian noise channel. Our scheme which has less decoding complexity than soft decoded COVQ systems, is shown to provide a notable signal-to-distortion ratio gain (up to 0.4 dB for memoryless Gaussian sources and up to 0.8 dB for Gauss-Markov sources) over the conventional COVQ designed for hard-decision demodulated channels.