• DocumentCode
    1038131
  • Title

    Adaptive channel estimation and equalization for rapidly mobile communication channels

  • Author

    El-Mahdy, Ahmed El-Sayed

  • Author_Institution
    Dept. of Electr. Eng., Mil. Tech. Coll., Cairo, Egypt
  • Volume
    52
  • Issue
    7
  • fYear
    2004
  • fDate
    7/1/2004 12:00:00 AM
  • Firstpage
    1126
  • Lastpage
    1135
  • Abstract
    This paper presents a reduced-complexity maximum-likelihood sequence estimation receiver, based on the Viterbi algorithm (VA), suitable for rapidly fading mobile communication channels. The channel impulse response is expanded onto a set of basis sequences and time-invariant (TI) expansion parameters. The proposed receiver continuously estimates the TI expansion parameters directly within the metric calculation of the VA. At every time instant of the VA, the accumulated metrics of the survivor paths are compared, and the survivors whose metrics are lower than the average value of the accumulated survivor metrics are retained. The other survivors are discarded from the trellis. Then the sequences associated with the minimum survivor of the retained survivors are used to update the estimate of the TI expansion parameters. The convergence properties of the estimation algorithm are investigated, and the steady-state value of the mean square error of estimation is derived. The performance of the proposed receiver is evaluated in terms of the symbol-error probability and compared with other receivers. The effects of time offset and frequency offset on the performance of the receiver are studied.
  • Keywords
    adaptive estimation; channel estimation; computational complexity; convergence of numerical methods; equalisers; error statistics; fading channels; least mean squares methods; maximum likelihood sequence estimation; mobile radio; radio receivers; recursive estimation; Viterbi algorithm; adaptive channel estimation; channel equalization; channel impulse response; convergence properties; frequency-selective fading channels; maximum-likelihood sequence estimation; mean square error estimation; minimum-survivor processing technique; mobile communication channels; parameter estimation; recursive least square approach; symbol-error probability; Adaptive equalizers; Channel estimation; Convergence; Estimation error; Fading; Maximum likelihood estimation; Mean square error methods; Mobile communication; Steady-state; Viterbi algorithm; Equalization; MLSE; frequency-selective fading channel; maximum-likelihood sequence estimation; parameter estimation;
  • fLanguage
    English
  • Journal_Title
    Communications, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0090-6778
  • Type

    jour

  • DOI
    10.1109/TCOMM.2004.831391
  • Filename
    1315913