On decoder-latency versus performance tradeoffs in differential predictive coding

Abstract

Theoretical analysis of differential predictive coding (DPC) has almost exclusively focused on scalar quantizers and the high-rate regime for tractability reasons. As a result, the role of noncausal decoding in improving the quality has been largely ignored in the literature. In this work we conduct a rigorous performance analysis of DPC-based schemes under a simple independent, vector-Gaussian, AR-1 source model and large-block (as opposed to high-rate) asymptotics. This analysis reveals that noncausal decoding can offer a significant relative improvement in the mean squared error (by as much as 3 dB) at medium to low rates (0.1-0.5 bit per sample) for sources having strong temporal correlation. Furthermore, most of this relative improvement can be attained with a modest decoder-latency. At very high and very low rates, the gains are negligible.