• DocumentCode
    3236143
  • Title

    Subspace based blind CFO estimation for OFDM by exploiting used carriers

  • Author

    Hiren, Gami ; Qasaymeh, M.M. ; Tayem, Nizar ; Pendse, Ravi ; Sawan, M.E.

  • Author_Institution
    EECS, Wichita State Univ., Wichita, KS
  • fYear
    2009
  • fDate
    March 30 2009-April 1 2009
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Orthogonal frequency division multiplexing (OFDM) is a promising technique to handle impairments of multipath channel. Alternatively, one of its major drawbacks is the drift in reference carrier, which is known as carrier frequency offset (CFO). Hence, the CFO should be estimated and compensated with a sufficient accuracy. In this paper, a new algorithm for blind CFO-OFDM estimation is obtained by introducing the propagator method (PM) in conjunction with the well-known MUSIC based high resolution searching algorithm. Furthermore, the PM does not require the eigenvalue decomposition (EVD) or singular value decomposition (SVD) of the covariance matrix of the received signals; Simulations are also included to demonstrate the effectiveness of the proposed method in comparison with other conventional methods.
  • Keywords
    OFDM modulation; covariance matrices; eigenvalues and eigenfunctions; estimation theory; multipath channels; signal classification; singular value decomposition; MUSIC; OFDM; carrier frequency offset; covariance matrix; eigenvalue decomposition; high resolution searching algorithm; multipath channel; orthogonal frequency division multiplexing; propagator method; singular value decomposition; subspace based blind CFO estimation; Communication standards; Discrete Fourier transforms; Eigenvalues and eigenfunctions; Fading; Frequency estimation; Multiple signal classification; OFDM modulation; Signal resolution; Singular value decomposition; USA Councils; DFT; Estimation; Frequency Offset; MUSIC; OFDM; Propagator Method;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Sarnoff Symposium, 2009. SARNOFF '09. IEEE
  • Conference_Location
    Princeton, NJ
  • Print_ISBN
    978-1-4244-3381-0
  • Electronic_ISBN
    978-1-4244-3382-7
  • Type

    conf

  • DOI
    10.1109/SARNOF.2009.4850278
  • Filename
    4850278