Iterative design of predictive vector quantizers for joint source-channel coding

A Lloyd-style iterative algorithm for designing predictive vector quantizers optimized to both source and channel is presented. We consider communication systems which use waveform channels and soft-decoding at the receiver. Based on reasonable assumptions, a set of conditions for the optimality of the predictive encoder and decoder, including the linear predictor, is derived. Simulation results based on a Gauss-Markov source and additive white Gaussian noise channel are presented. These results show that, when hard-decoding is used, the predictive codes designed here perform nearly identically to those obtained by gradient-search optimization techniques. It is also demonstrated that soft-decoding based systems designed with the proposed algorithm significantly outperform the hard-decoding systems.

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