On Predictive Coding for Erasure Channels Using a Kalman Framework
(2009) In IEEE Transactions on Signal Processing 57(11). p.4456-4466- Abstract
- We present a new design method for robust low-delay coding of autoregressive (AR) sources for transmission across erasure channels. It is a fundamental rethinking of existing concepts. It considers the encoder a mechanism that produces signal measurements from which the decoder estimates the original signal. The method is based on linear predictive coding and Kalman estimation at the decoder. We employ a novel encoder state-space representation with a linear quantization noise model. The encoder is represented by the Kalman measurement at the decoder. The presented method designs the encoder and decoder offline through an iterative algorithm based on closed-form minimization of the trace of the decoder state error covariance. The design... (More)
- We present a new design method for robust low-delay coding of autoregressive (AR) sources for transmission across erasure channels. It is a fundamental rethinking of existing concepts. It considers the encoder a mechanism that produces signal measurements from which the decoder estimates the original signal. The method is based on linear predictive coding and Kalman estimation at the decoder. We employ a novel encoder state-space representation with a linear quantization noise model. The encoder is represented by the Kalman measurement at the decoder. The presented method designs the encoder and decoder offline through an iterative algorithm based on closed-form minimization of the trace of the decoder state error covariance. The design method is shown to provide 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. The design method applies to stationary auto-regressive sources of any order. We demonstrate the method in a framework based on a generalized differential pulse code modulation (DPCM) encoder. The presented principles can be applied to more complicated coding systems that incorporate predictive coding as well. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/4092469
- author
- Arildsen, Thomas ; Murthi, Manohar N. ; Andersen, Sören Vang LU and Jensen, Soren Holdt
- publishing date
- 2009
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Differential pulse code modulation (DPCM), erasure channels, joint, source-channel coding, Kalman filtering, linear predictive coding, quantization
- in
- IEEE Transactions on Signal Processing
- volume
- 57
- issue
- 11
- pages
- 4456 - 4466
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- external identifiers
-
- wos:000270747200026
- scopus:70350517766
- ISSN
- 1053-587X
- DOI
- 10.1109/TSP.2009.2025796
- language
- English
- LU publication?
- no
- id
- 42327e25-bbd0-4925-b426-5b07b40f4337 (old id 4092469)
- date added to LUP
- 2016-04-01 14:20:31
- date last changed
- 2022-01-28 00:07:33
@article{42327e25-bbd0-4925-b426-5b07b40f4337,
abstract = {{We present a new design method for robust low-delay coding of autoregressive (AR) sources for transmission across erasure channels. It is a fundamental rethinking of existing concepts. It considers the encoder a mechanism that produces signal measurements from which the decoder estimates the original signal. The method is based on linear predictive coding and Kalman estimation at the decoder. We employ a novel encoder state-space representation with a linear quantization noise model. The encoder is represented by the Kalman measurement at the decoder. The presented method designs the encoder and decoder offline through an iterative algorithm based on closed-form minimization of the trace of the decoder state error covariance. The design method is shown to provide 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. The design method applies to stationary auto-regressive sources of any order. We demonstrate the method in a framework based on a generalized differential pulse code modulation (DPCM) encoder. The presented principles can be applied to more complicated coding systems that incorporate predictive coding as well.}},
author = {{Arildsen, Thomas and Murthi, Manohar N. and Andersen, Sören Vang and Jensen, Soren Holdt}},
issn = {{1053-587X}},
keywords = {{Differential pulse code modulation (DPCM); erasure channels; joint; source-channel coding; Kalman filtering; linear predictive coding; quantization}},
language = {{eng}},
number = {{11}},
pages = {{4456--4466}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
series = {{IEEE Transactions on Signal Processing}},
title = {{On Predictive Coding for Erasure Channels Using a Kalman Framework}},
url = {{http://dx.doi.org/10.1109/TSP.2009.2025796}},
doi = {{10.1109/TSP.2009.2025796}},
volume = {{57}},
year = {{2009}},
}