Power series quantization for noisy channels

A recently proposed method for transmission of correlated sources under noise-free conditions, power series quantization (PSQ), uses a separate linear or nonlinear predictor for each quantizer region, and has shown to increase performance compared to several common quantization schemes for sources with memory. In this paper, it is shown how to apply PSQ for transmission of a source with memory over a noisy channel. A channel-optimized PSQ (COPSQ) encoder and codebook optimization algorithms are derived. The suggested scheme is shown to increase performance compared with previous state-of-the- art methods.