• DocumentCode
    3157028
  • Title

    Robust maximin MIMO precoding for arbitrary convex uncertainty sets

  • Author

    Wang, Jiaheng ; Bengtsson, Mats ; Ottersten, Björn ; Palomar, Daniel P.

  • Author_Institution
    Nat. Mobile Commun. Res. Lab., Southeast Univ., Nanjing, China
  • fYear
    2012
  • fDate
    25-30 March 2012
  • Firstpage
    3045
  • Lastpage
    3048
  • Abstract
    We consider a worst-case robust precoding design for multi-input multi-output (MIMO) communication systems with imperfect channel state information at the transmitter (CSIT). Instead of a particular choice, we consider a general imperfect CSIT model that only assumes the channel errors to be within a convex set, which includes most common imperfect CSIT models as special cases. The robust precoding design is formulated as a maximin problem, aiming at maximizing the worst-case received signal-to-noise ratio or minimizing the worst-case error probability. It is shown that the robust precoder can be easily obtained by solving a convex problem. We further provide an equivalent but more practical form of the convex problem that can be efficiently handled with common optimization methods and software packages.
  • Keywords
    MIMO communication; convex programming; error statistics; minimax techniques; precoding; radio transmitters; wireless channels; CSIT model; arbitrary convex uncertainty sets; channel state information at the transmitter model; multiinput multioutput communication systems; robust maximin MIMO precoding; software packages; worst-case error probability; worst-case received signal-to-noise ratio; worst-case robust precoding; Convex functions; MIMO; Robustness; Signal to noise ratio; Software packages; Transmitters; Uncertainty; Convex uncertainty sets; MIMO; imperfect CSIT; maximin; worst-case robustness;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on
  • Conference_Location
    Kyoto
  • ISSN
    1520-6149
  • Print_ISBN
    978-1-4673-0045-2
  • Electronic_ISBN
    1520-6149
  • Type

    conf

  • DOI
    10.1109/ICASSP.2012.6288557
  • Filename
    6288557