Noisy channel relaxation for VQ design

We study the structure and design of a vector quantizer (VQ) for robust performance under noisy channel conditions. We develop some new insights about the geometrical structure of such a VQ, and introduce noisy channel relaxation-a novel design approach. In particular, the approach is used to attack two basic problems: (1) optimize the VQ for a given noisy channel; and (2) optimize index assignment while maintaining optimality for the noiseless channel. For problem (1) we show consistent improvements over descent methods at the cost of manageable increase in complexity (by a factor of up to three). For problem (2) we obtain index assignment with a quality significantly better than known methods, but at computational complexity that grows many times slower