• DocumentCode
    1696145
  • Title

    A Novel Adaptive Detection Algorithm Jointly Utilizing Channel Estimation for MIMO System in Continuous Flat Fading Channels

  • Author

    Yang Gao ; Hongming Zheng ; Feng Zhou ; Yongkang Gao ; Xiaoyun Wu

  • Author_Institution
    CTL, Beijing
  • fYear
    2008
  • Firstpage
    439
  • Lastpage
    444
  • Abstract
    The Vertical Bell Laboratories Layered Space-Time (V-BLAST) system can provide high capacity over rich scattering channel. The conventional minimum mean square error (MMSE) detection for V-BLAST is not suitable for time-varying channel due to high complexity. In the paper, we proposed an adaptive detection algorithm, which combines maximum likelihood (ML) channel estimator and least mean squares (LMS) algorithm together. The proposed adaptive methodology can also be used in the base station (BS) of the MIMO-MU system, where the V-BLAST adaptive receiver and the transmitting preprocessing technique are jointly designed in BS with MIMO-MU detection over time-varying channels. From the simulations, we can see the proposed detection method can outperform the conventional MMSE detection with lower complexity.
  • Keywords
    MIMO communication; channel estimation; fading channels; least mean squares methods; maximum likelihood estimation; time-varying channels; MIMO system; MMSE detection; Vertical Bell Laboratories Layered Space-Time system; adaptive detection algorithm; adaptive methodology; adaptive receiver; base station; channel scattering; continuous flat fading channel; least mean squares algorithm; maximum likelihood channel estimator; minimum mean square error; preprocessing technique; time-varying channel; Channel estimation; Detection algorithms; Fading; Least squares approximation; MIMO; Maximum likelihood detection; Maximum likelihood estimation; Mean square error methods; Scattering; Time-varying channels;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems for Communications, 2008. ICCSC 2008. 4th IEEE International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-1707-0
  • Electronic_ISBN
    978-1-4244-1708-7
  • Type

    conf

  • DOI
    10.1109/ICCSC.2008.100
  • Filename
    4536792