Maximum Likelihood Estimation of Carrier Frequency Offset in Correlated MIMO OFDM Systems

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 ar...

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Bibliographic Details
Main Authors: Zeng, X.N., Ghrayeb, A.
Format: Conference Proceeding
Language:English
Subjects:
AWGN
Cost function
Fading
Frequency estimation
Maximum likelihood estimation
MIMO
OFDM
Receiving antennas
Transmitting antennas
Unified modeling language
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Summary: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 Cram r-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
ISSN:2162-3562
2162-3570
DOI:10.1109/SIPS.2006.352554