DocumentCode :
3120164
Title :
Broadcast correlated Gaussians: The vector-scalar case
Author :
Song, Lin ; Chen, Jun ; Tian, Chao
Author_Institution :
McMaster Univ., Hamilton, ON, Canada
fYear :
2012
fDate :
1-6 July 2012
Firstpage :
199
Lastpage :
203
Abstract :
The problem of sending a set of correlated Gaussian sources over a bandwidth-matched two-user scalar Gaussian broadcast channel is studied in this work, where the strong receiver wishes to reconstruct several source components (i.e., a vector source) under a distortion covariance matrix constraint and the weak receiver wishes to reconstruct a single source component (i.e., a scalar source) under the mean squared error distortion constraint. We provide a complete characterization of the optimal tradeoff between the transmit power and the achievable reconstruction distortion pair for this problem. The converse part is based on a new bounding technique which involves the introduction of an appropriate remote source. The forward part is based on a hybrid scheme where the digital portion uses dirty paper channel code and Wyner-Ziv source code. This scheme is different from the optimal scheme proposed by Tian et al. in a recent work for the scalar-scalar case, which implies that the optimal scheme for the scalar-scalar case is in fact not unique.
Keywords :
Gaussian channels; broadcast channels; channel coding; covariance matrices; mean square error methods; source coding; Gaussian broadcast channel; Wyner-Ziv source code; bandwidth-matched broadcast channel; broadcast correlated Gaussians; correlated Gaussian sources; digital portion; dirty paper channel code; distortion covariance matrix constraint; mean squared error distortion constraint; optimal tradeoff; receiver; single source component; transmit power; two-user scalar broadcast channel; vector source; vector-scalar case; Covariance matrix; Decoding; Encoding; Joints; Random variables; Receivers; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Theory Proceedings (ISIT), 2012 IEEE International Symposium on
Conference_Location :
Cambridge, MA
ISSN :
2157-8095
Print_ISBN :
978-1-4673-2580-6
Electronic_ISBN :
2157-8095
Type :
conf
DOI :
10.1109/ISIT.2012.6283650
Filename :
6283650
Link To Document :
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