Maximum Likelihood Estimation of Carrier Frequency Offset in Correlated MIMO OFDM SystemsThis work was supported in part by NSERC Grant N00858 and an NSERC Canada Graduate Scholarship. Conference Paper uri icon


  • This paper discusses maximum likelihood (ML) carrier frequency offset (CFO) estimation based on virtual subcarriers for multiple-input multiple-output (MIMO) systems employing orthogonal frequency division multiplexing (OFDM) over Rayleigh fading channels. In our ML approach, the channel and data are treated as random variables, unlike existing ML approaches in which the channel and data are treated as unknown constants. This in turn enables us to incorporate the spatial correlation and transmit data correlation into the analysis. In particular, we derive closed-form cost functions which can be used to accurately estimate the CFO. We also derive the Cramr-Rao lower bounds (CRLBs) for these estimators. We show that the presence of these correlations does not impact the CFO estimation significantly, especially at high signal-to-noise ratio. We present several examples to support the analysis. 2006 IEEE.

name of conference

  • 2006 IEEE Workshop on Signal Processing Systems Design and Implementation

published proceedings

  • 2010 IEEE Workshop On Signal Processing Systems

author list (cited authors)

  • Zeng, X. N., & Ghrayeb, A.

citation count

  • 0

complete list of authors

  • Zeng, Xiang Nian||Ghrayeb, Ali

publication date

  • October 2006