• DocumentCode
    2943980
  • Title

    An Extremal Inequality Motivated by Multiterminal Information Theoretic Problems

  • Author

    Liu, Tie ; Viswanath, Pramod

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Illinois Univ., Urbana, IL
  • fYear
    2006
  • fDate
    9-14 July 2006
  • Firstpage
    1016
  • Lastpage
    1020
  • Abstract
    We prove a new extremal inequality, motivated by the vector Gaussian broadcast channel and the distributed source coding with a single quadratic distortion constraint problem. As a corollary, this inequality yields a generalization of the classical vector entropy-power inequality (EPI). As another corollary, this inequality sheds insight into maximizing differential entropy of a sum of jointly distributed random variables, generalizing a classical result of Cover and Zhang
  • Keywords
    Gaussian channels; broadcast channels; combined source-channel coding; entropy; differential entropy; distributed source coding; extremal inequality; multiterminal information theoretic problems; quadratic distortion constraint; vector Gaussian broadcast channel; vector entropy-power inequality; Additive noise; Broadcasting; Channel capacity; Constraint theory; Covariance matrix; Distributed computing; Entropy; Random variables; Source coding; Symmetric matrices;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Theory, 2006 IEEE International Symposium on
  • Conference_Location
    Seattle, WA
  • Print_ISBN
    1-4244-0505-X
  • Electronic_ISBN
    1-4244-0504-1
  • Type

    conf

  • DOI
    10.1109/ISIT.2006.261881
  • Filename
    4036118