• DocumentCode
    1086994
  • Title

    Code-aided quasi-maximum SINR algorithms for blind linear multiuser detection

  • Author

    Zhu, S. ; Constantinides, A.G.

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Commun. & Signal Process. Group, London
  • Volume
    1
  • Issue
    4
  • fYear
    2007
  • fDate
    8/1/2007 12:00:00 AM
  • Firstpage
    638
  • Lastpage
    646
  • Abstract
    The problem of blind linear data-symbol estimation and data detection for the air- interface adopting the wide-band direct sequence code division multiple access multiuser multiplexing technique with the promising short-code configurations has been addressed. The superior interference-suppression ability of the code-constrained minimum output energy multipath- component estimation is utilised to develop three code-aided quasi-maximum signal-to-interference and noise ratio (SINR) algorithms. These algorithms operate in such a way as to maximise approximate measures of the output SINR, each having variations, especially in the adaptive implementation, because of different criteria employed. The ´quasi-maximum SINR´ nature is because of the approximations employed. Extensive simulations indicate that all of these algorithms significantly outperform the existing code-aided blind linear algorithms at considerably low computational complexity. Moreover their adaptive versions exhibit very high level of desirable trade-off between convergence speed and steady-state performance at further reduced computational complexity.
  • Keywords
    broadband networks; code division multiple access; code division multiplexing; interference suppression; multiuser detection; blind linear data-symbol estimation; blind linear multiuser detection; code-aided quasimaximum SINR algorithms; computational complexity; data detection; interference-suppression; multipath-component estimation; multiuser multiplexing technique; wide-band direct sequence code division multiple access;
  • fLanguage
    English
  • Journal_Title
    Communications, IET
  • Publisher
    iet
  • ISSN
    1751-8628
  • Type

    jour

  • DOI
    10.1049/iet-com:20060022
  • Filename
    4286617