• DocumentCode
    787224
  • Title

    MIMO channel modeling and the principle of maximum entropy

  • Author

    Debbah, Mérouane ; Müller, Ralf R.

  • Author_Institution
    Mobile Commun. Group, Inst. Eurecom, B.P, Sophia-Antipolis, France
  • Volume
    51
  • Issue
    5
  • fYear
    2005
  • fDate
    5/1/2005 12:00:00 AM
  • Firstpage
    1667
  • Lastpage
    1690
  • Abstract
    We devise theoretical grounds for constructing channel models for multiple-input multiple-output (MIMO) systems based on information-theoretic tools. The paper provides a general method to derive a channel model which is consistent with one´s state of knowledge. The framework we give here has already been fruitfully explored with success in the context of Bayesian spectrum analysis and parameter estimation. For each channel model, we conduct an asymptotic analysis (in the number of antennas) of the achievable transmission rate using tools from random matrix theory. A central limit theorem is provided on the asymptotic behavior of the mutual information and validated in the finite case by simulations. The results are useful both in terms of designing a system based on criteria such as quality of service and in optimizing transmissions in multiuser networks.
  • Keywords
    MIMO systems; antenna arrays; belief networks; matrix algebra; maximum entropy methods; probability; quality of service; random processes; telecommunication channels; Bayesian spectrum analysis; MIMO channel modeling; antenna arrays; asymptotic analysis; information-theoretic tools; maximum entropy principle; multiple-input multiple-output; parameter estimation; probability theory; quality of service; random matrix theory; Antennas and propagation; Bayesian methods; Entropy; MIMO; Mobile communication; Receiving antennas; Signal processing; Signal to noise ratio; Transmitters; Transmitting antennas; Antenna arrays; Bayesian probability theory; channel modeling; entropy; multiple-input multiple-output (MIMO); random matrices;
  • fLanguage
    English
  • Journal_Title
    Information Theory, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9448
  • Type

    jour

  • DOI
    10.1109/TIT.2005.846388
  • Filename
    1424308