• DocumentCode
    3257175
  • Title

    Improved carrier frequency offset estimator for common referenced sampling and RF oscillators in OFDM transceivers

  • Author

    Jin Yuan ; Torlak, Murat

  • Author_Institution
    Dept. of Electr. Eng., Univ. of Texas at Dallas, Richardson, TX, USA
  • fYear
    2013
  • fDate
    3-5 Dec. 2013
  • Firstpage
    1174
  • Lastpage
    1177
  • Abstract
    Orthogonal frequency division multiplexing (OFDM) has been proven to be very sensitive to carrier drifts due to fact that both carrier frequency offset (CFO) and sampling frequency offset (SFO) destroy the orthogonality cross multiple subcarriers. The sampling clock and the local oscillator, from which the carrier frequency is derived, sharing a common reference clock is becoming a configuration extensively used in wireless transceivers. In this paper, we propose a maximum likelihood (ML) estimation scheme with the common reference clock assumption. We further propose two CFO estimators with low computational complexity - a near ML estimator and a method of moments estimator. With the common reference clock assumption, the CFO estimation range is widened to many multiples of subcarrier spacing without any additional training symbols or constructing the training symbol by multiple identical parts. The performance of the proposed algorithms in comparison with existing estimators is studied through simulations. The proposed algorithms are validated on a real-time hardware testbed.
  • Keywords
    OFDM modulation; maximum likelihood estimation; method of moments; transceivers; CFO estimators; OFDM transceivers; RF oscillators; SFO; common referenced sampling; improved carrier frequency offset estimator; local oscillator; low computational complexity; maximum likelihood estimation scheme; method of moments estimator; near ML estimator; orthogonal frequency division multiplexing; sampling clock; sampling frequency offset; Clocks; Covariance matrices; Frequency division multiplexing; Maximum likelihood estimation; OFDM; Training; CFO estimation; OFDM; SFO; maximum likelihood (ML); method of moments estimator;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Global Conference on Signal and Information Processing (GlobalSIP), 2013 IEEE
  • Conference_Location
    Austin, TX
  • Type

    conf

  • DOI
    10.1109/GlobalSIP.2013.6737116
  • Filename
    6737116