On predictive coding for erasure channels using a Kalman framework

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

Research output: Contribution to journalConference articlepeer-review


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 offline 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 (US)
Pages (from-to)1646-1650
Number of pages5
JournalEuropean Signal Processing Conference
StatePublished - Dec 1 2009
Event17th European Signal Processing Conference, EUSIPCO 2009 - Glasgow, United Kingdom
Duration: Aug 24 2009Aug 28 2009

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering


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