• DocumentCode
    2904010
  • Title

    Linear Prediction Based Semi-Blind Channel Estimation for MIMO-OFDM System

  • Author

    Wan, Feng ; Zhu, Wei-Ping ; Swamy, M.N.S.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Concordia Univ., Montreal, Que.
  • fYear
    2007
  • fDate
    27-30 May 2007
  • Firstpage
    3239
  • Lastpage
    3242
  • Abstract
    In this paper, a semi-blind channel estimation method is presented for MIMO-OFDM systems. The new method uses the linear prediction for obtaining a blind constraint on the MIMO-OFDM channel matrix as well as the least-squares approximation for the training signal. The proposed method can be regarded as an extension of an existing semi-blind MIMO channel estimation algorithm. Yet the extension is nontrivial, since the formulation of the MIMO-OFDM signal and the related blind constraint cannot easily be obtained from the MIMO counterpart. The proposed algorithm is simulated using Monte-Carlo method and compared with the LS method in terms of the mean square error (MSE) of the estimation. Simulation results show that the proposed method consistently outperforms the LS method when the same training signal is used.
  • Keywords
    MIMO communication; Monte Carlo methods; OFDM modulation; blind source separation; channel estimation; least squares approximations; mean square error methods; MIMO-OFDM system; Monte-Carlo method; blind constraint; least-squares approximation; linear prediction; mean square error; semiblind channel estimation; Blind equalizers; Channel estimation; Least squares approximation; MIMO; Maximum likelihood estimation; Mean square error methods; Receiving antennas; Signal processing algorithms; Transmitting antennas; Wireless communication;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 2007. ISCAS 2007. IEEE International Symposium on
  • Conference_Location
    New Orleans, LA
  • Print_ISBN
    1-4244-0920-9
  • Electronic_ISBN
    1-4244-0921-7
  • Type

    conf

  • DOI
    10.1109/ISCAS.2007.378162
  • Filename
    4253369