On decoder-latency versus performance tradeoffs in differential predictive coding (MP-P8)

Author(s) : Prakash Ishwar (University of California, Berkeley, USA) Kannan Ramchandran (University of California, Berkeley, USA)

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 non-causal 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 non-causal decoding can offer a significant relative improvement in the mean squared error (by as much as 3 dB) at medium rates (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. Interestingly, the peak gain is attained at 0.5 bit per sample irrespective of the temporal correlation.

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