• 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