• DocumentCode
    3167757
  • Title

    The problem of prediction methods for time-domain blind identification of multichannel FIR filters

  • Author

    Xu, YiLing ; Peng, Qicong

  • Author_Institution
    Inst. of Commun. & Inf. Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
  • Volume
    2
  • fYear
    2002
  • fDate
    29 June-1 July 2002
  • Firstpage
    881
  • Abstract
    The concept of linear estimation for SIMO systems was first presented by D. Slock (see Proc. 1994 IEEE ICASSP, vol.IV, p.585-8, 1994; Proc. 1994 Asilomar Conf. on Signals, Systems and Computers, p.1154-8, 1994). Later, a linear prediction channel identification algorithm was developed by K. Abed-Meraim et al. (see Proc. 1995 IEEE ICASSP, p.1968-71, 1995). This blind channel identification algorithm uses only second order statistics, so it is a breakthrough in this field and has been cited frequently by others. But the simulation of the algorithm developed by Abed-Meraim et al. shows that the channel could not be identified because there is still needed another condition, which could not be obtained for knowing nothing about the channel in the whole blind condition.
  • Keywords
    FIR filters; channel estimation; equalisers; estimation theory; prediction theory; statistical analysis; time-domain analysis; SIMO systems; blind identification; channel equalization; linear estimation; linear prediction channel identification algorithm; multichannel FIR filters; multichannel filters; prediction methods; second order statistics; time-domain; Finite impulse response filter; Higher order statistics; Information filtering; Information filters; Nonlinear filters; Polynomials; Prediction algorithms; Prediction methods; Time domain analysis; White noise;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communications, Circuits and Systems and West Sino Expositions, IEEE 2002 International Conference on
  • Print_ISBN
    0-7803-7547-5
  • Type

    conf

  • DOI
    10.1109/ICCCAS.2002.1178929
  • Filename
    1178929