On Predictive Coding for Erasure Channels Using a Kalman Framework

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

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Resumé

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.
OriginalsprogEngelsk
TitelProceedings of the 17th European Signal Processing Conference (EUSIPCO-2009)
ForlagUniversity of Strathclyde
Publikationsdato2009
Sider1646-1650
StatusUdgivet - 2009
BegivenhedEuropean Signal Processing Conference - Glasgow, Storbritannien
Varighed: 24 aug. 200928 aug. 2009
Konferencens nummer: 17

Konference

KonferenceEuropean Signal Processing Conference
Nummer17
LandStorbritannien
ByGlasgow
Periode24/08/200928/08/2009
NavnProceedings of the European Signal Processing Conference
ISSN2076-1465

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Decoding
Signal to noise ratio

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Online proceedings

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Arildsen, T., Murthi, M., Andersen, S. V., & Jensen, S. H. (2009). On Predictive Coding for Erasure Channels Using a Kalman Framework. I Proceedings of the 17th European Signal Processing Conference (EUSIPCO-2009) (s. 1646-1650). University of Strathclyde. Proceedings of the European Signal Processing Conference
Arildsen, Thomas ; Murthi, Manohar ; Andersen, Søren Vang ; Jensen, Søren Holdt. / On Predictive Coding for Erasure Channels Using a Kalman Framework. Proceedings of the 17th European Signal Processing Conference (EUSIPCO-2009). University of Strathclyde, 2009. s. 1646-1650 (Proceedings of the European Signal Processing Conference).
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abstract = "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.",
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Arildsen, T, Murthi, M, Andersen, SV & Jensen, SH 2009, On Predictive Coding for Erasure Channels Using a Kalman Framework. i Proceedings of the 17th European Signal Processing Conference (EUSIPCO-2009). University of Strathclyde, Proceedings of the European Signal Processing Conference, s. 1646-1650, European Signal Processing Conference, Glasgow, Storbritannien, 24/08/2009.

On Predictive Coding for Erasure Channels Using a Kalman Framework. / Arildsen, Thomas; Murthi, Manohar; Andersen, Søren Vang; Jensen, Søren Holdt.

Proceedings of the 17th European Signal Processing Conference (EUSIPCO-2009). University of Strathclyde, 2009. s. 1646-1650 (Proceedings of the European Signal Processing Conference).

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

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N2 - 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.

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Arildsen T, Murthi M, Andersen SV, Jensen SH. On Predictive Coding for Erasure Channels Using a Kalman Framework. I Proceedings of the 17th European Signal Processing Conference (EUSIPCO-2009). University of Strathclyde. 2009. s. 1646-1650. (Proceedings of the European Signal Processing Conference).