Robust vector quantization for wireless channels

Abstract

This study focuses on two issues: parametric modeling of the channel and index assignment of codevectors, to design a vector quantizer that achieves high robustness against channel errors. We first formulate the design of a robust zero-redundancy vector quantizer as a combinatorial optimization problem leading to a genetic search for a minimum-distortion index assignment. Performance is further enhanced by the use of the Fritchman channel model that more closely characterizes the statistical dependencies between error sequences. This study also presents an index assignment algorithm based on the Fritchman model with parameter values estimated using a real-coded genetic algorithm. Simulation results indicate that the global explorative properties of genetic algorithms make them very effective in estimating Fritchman model parameters, and use of this model can match index assignment to expected channel conditions.