• DocumentCode
    416397
  • Title

    A novel integer frequency offset estimator for OFDM

  • Author

    Chen, Chen ; Li, Jiandong ; Han, Gang

  • Author_Institution
    Broadband Wireless Commun. Lab., Xidian Univ., Xi´´an, China
  • Volume
    1
  • fYear
    2004
  • fDate
    31 May-2 June 2004
  • Firstpage
    29
  • Abstract
    A novel estimator for integer frequency offset estimation of OFDM systems is derived, which is based on maximum likelihood (ML) technique and exploits the differential information between two consecutive OFDM data symbols sequences in frequency domain. The reason why the ML estimator has better performance than the conventional method is analyzed. The effects of integer frequency offset, system parameters, and differential PN sequence on the performances of the two estimators are analyzed. How to select the differential sequence is also studied. By computer simulations, the performance of the ML estimator is compared with that of the conventional method for the additive white Gaussian noise (AWGN) channel and a multipath fading channel. The simulation results are in good agreement with the analytical study.
  • Keywords
    AWGN channels; OFDM modulation; fading channels; frequency estimation; maximum likelihood estimation; multipath channels; OFDM data symbols sequence; OFDM system; additive white Gaussian noise channel; differential PN sequence; integer frequency offset estimator; maximum likelihood technique; multipath fading channel; orthogonal frequency division multiplexing; AWGN; Additive white noise; Computational modeling; Computer simulation; Fading; Frequency domain analysis; Frequency estimation; Maximum likelihood estimation; OFDM; Performance analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Emerging Technologies: Frontiers of Mobile and Wireless Communication, 2004. Proceedings of the IEEE 6th Circuits and Systems Symposium on
  • Print_ISBN
    0-7803-7938-1
  • Type

    conf

  • DOI
    10.1109/CASSET.2004.1322909
  • Filename
    1322909