• DocumentCode
    1762503
  • Title

    Broadcasting Correlated Vector Gaussians

  • Author

    Lin Song ; Jun Chen ; Chao Tian

  • Author_Institution
    Dept. of Electr. & Comput. Eng., McMaster Univ., Hamilton, ON, Canada
  • Volume
    61
  • Issue
    5
  • fYear
    2015
  • fDate
    42125
  • Firstpage
    2465
  • Lastpage
    2477
  • Abstract
    The problem of sending two correlated vector Gaussian sources over a bandwidth-matched two-user scalar Gaussian broadcast channel is studied in this paper, where each receiver wishes to reconstruct its target source under a covariance distortion constraint. We derive a lower bound on the optimal tradeoff between the transmit power and the achievable reconstruction distortion pair. Our derivation is based on a new bounding technique which involves the introduction of appropriate remote sources. Furthermore, it is shown that this lower bound is achievable by a class of hybrid schemes for the special case, where the weak receiver wishes to reconstruct a scalar source under the mean squared error distortion constraint.
  • Keywords
    Gaussian channels; broadcast channels; mean square error methods; vectors; achievable reconstruction distortion pair; bandwidth-matched two-user scalar Gaussian broadcast channel; bounding technique; correlated vector Gaussian sources; covariance distortion constraint; hybrid schemes; mean squared error distortion constraint; optimal tradeoff; remote sources; scalar source; transmit power; Covariance matrices; Decoding; Encoding; Receivers; Tin; Vectors; Zinc; Broadcast channel; Gaussian source; Wyner-Ziv coding; Wyner-Ziv coding.; dirty paper coding; joint source-channel coding;
  • fLanguage
    English
  • Journal_Title
    Information Theory, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9448
  • Type

    jour

  • DOI
    10.1109/TIT.2015.2412540
  • Filename
    7059240