Distributed Remote Vector Gaussian Source Coding for Wireless Acoustic Sensor Networks

Adel Zahedi, Jan Østergaard, Søren Holdt Jensen, Patrick Naylor, Søren Bech

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6 Citationer (Scopus)
278 Downloads (Pure)

Abstract

In this paper, we consider the problem of remote vector Gaussian source coding for a wireless acoustic sensor network. Each node receives messages from multiple nodes in the network and decodes these messages using its own measurement of the sound field as side information. The node's measurement and the estimates of the source resulting from decoding the received messages are then jointly encoded and transmitted to a neighbouring node in the network. We show that for this distributed source coding scenario, one can encode a so-called conditional sufficient statistic of the sources instead of jointly encoding multiple sources. We focus on the case where node measurements are in form of noisy linearly mixed combinations of the sources and the acoustic channel mixing matrices are invertible. For this problem, we derive the rate-distortion function for vector Gaussian sources and under covariance distortion constraints.
OriginalsprogEngelsk
TitelData Compression Conference (DCC), 2014
Antal sider10
ForlagIEEE Press
Publikationsdatomar. 2014
Sider263-272
DOI
StatusUdgivet - mar. 2014
Begivenhed2014 Data Compression Conference - Snowbird, Utah, USA
Varighed: 26 mar. 201428 mar. 2014
Konferencens nummer: 31565

Konference

Konference2014 Data Compression Conference
Nummer31565
Land/OmrådeUSA
BySnowbird, Utah
Periode26/03/201428/03/2014
NavnData Compression Conference. Proceedings
ISSN1068-0314

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