A Semiblind Channel Estimation Approach for MIMO-OFDM Systems

In this paper, a very efficient semiblind approach that uses a training-based least square criterion along with a blind constraint is proposed for multiple-input-multiple-output-orthogonal frequency-division multiplexing (MIMO-OFDM) channel estimation. The blind constraint is derived from the linear...

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Bibliographic Details
Published in:IEEE transactions on signal processing 2008-07, Vol.56 (7), p.2821-2834
Main Authors: Feng Wan, Zhu, W.-P., Swamy, M.N.S.
Format: Article
Language:English
Subjects:
Applied sciences
Channel estimation
Detection, estimation, filtering, equalization, prediction
Exact sciences and technology
Frequency division multiplexing
Frequency estimation
Information, signal and communications theory
Least squares approximation
Mean square error methods
MIMO-orthogonal frequency-division multiplexing (MIMO-OFDM)
Miscellaneous
multiple-input-multiple-output (MIMO) linear prediction
Multiplexing
OFDM
perturbation analysis
Receiving antennas
semiblind
Signal and communications theory
Signal processing
Signal processing algorithms
Signal, noise
Statistics
Telecommunications and information theory
Vectors
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Summary:In this paper, a very efficient semiblind approach that uses a training-based least square criterion along with a blind constraint is proposed for multiple-input-multiple-output-orthogonal frequency-division multiplexing (MIMO-OFDM) channel estimation. The blind constraint is derived from the linear prediction of the received MIMO-OFDM signal and is used in conjunction with a weighting factor in the semiblind cost function. An appealing scheme for the determination of the weighting factor is presented as a part of the proposed approach. A perturbation analysis of the proposed method is conducted to justify the superiority of the semiblind solution and to obtain a closed-form expression for the mean square error (MSE) of the blind constraint, further facilitating the calculation of the weighting factor. The proposed method is validated through computer simulation-based experimentations, showing a very high estimation accuracy of the semiblind solution in terms of the MSE of the channel estimate.
ISSN:1053-587X
1941-0476
DOI:10.1109/TSP.2008.917354