On Predictive Coding for Erasure Channels Using a Kalman Framework

Thomas Arildsen, Manohar Murthi, Søren Vang Andersen, Søren Holdt Jensen

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We present a new design method for robust low-delay coding of auto-regressive (AR) sources for transmission across erasure channels. The method is based on Linear Predictive Coding (LPC) with Kalman estimation at the decoder. The method designs the encoder and decoder off-line through an iterative algorithm based on minimization of the trace of the decoder state error covariance. The design method applies to stationary AR sources of any order. Simulation results show considerable performance gains, when the transmitted quantized prediction errors are subject to loss, in terms of Signal-to-Noise Ratio (SNR) compared to the same coding framework optimized for no loss. We furthermore investigate the impact on decoding performance when channel losses are correlated. We find that the method still provides substantial improvements in this case despite being designed for i.i.d. losses.
Original languageEnglish
Title of host publicationProceedings of the 17th European Signal Processing Conference (EUSIPCO-2009)
PublisherUniversity of Strathclyde
Publication date2009
Publication statusPublished - 2009
EventEuropean Signal Processing Conference - Glasgow, United Kingdom
Duration: 24 Aug 200928 Aug 2009
Conference number: 17


ConferenceEuropean Signal Processing Conference
Country/TerritoryUnited Kingdom
SeriesProceedings of the European Signal Processing Conference


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