Price of Perfection: Limited Prediction for Streaming Over Erasure Channels

We study sequential transmission of Gauss-Markov sources over erasure channels under a zero decoding delay constraint. A two-stage coding scheme which can be described as a hybrid between predictive coding with limited past and quantization & binning is proposed. This scheme can achieve significant performance gains over baseline schemes in simulations involving i.i.d. erasure channels, and in certain regimes can attain performance close to a fundamental lower bound. We consider an information theoretic model for streaming that explains the weakness of baseline schemes (e.g., predictive coding, memoryless binning, etc.) and illustrates the advantage of our proposed hybrid scheme over these. Techniques from multi-terminal source coding are used to derive a new lower bound on the compression rate and identify cases when the hybrid coding scheme is close to optimal. We discuss qualitatively the interplay between the parameters of our information theoretic model and the statistical models used in simulations.