文档介绍：ARTICLE IN PRESS
Signal Processing 90 (2010) 1861–1872
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Signal Processing
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A Krylov subspace based low-rank channel estimation
in OFDM systems
J. Oliver Ã, R. Aravind, . Prabhu
Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai 600 036, India
article info abstract
Article history: We investigate a low-rank minimum mean-square error (MMSE) channel estimator in
Received 28 April 2009 orthogonal frequency division multiplexing (OFDM) systems. The proposed estimator is
Received in revised form derived by using the multi-stage nested Wiener filter (MSNWF) identified in the
7 December 2009 literature as a Krylov subspace approach for rank reduction. We describe the low-rank
Accepted 7 December 2009
MMSE expressions for exploiting the time correlation function (TCF) of the channel path
Available online 16 December 2009
gains. The Krylov subspace technique requires neither eigenvalue decomposition (EVD)
Keywords: nor the inverse of the covariance matrices for parameter estimation. We show that the
Channel estimation Krylov channel estimator can perform as well as the EVD estimator with a much smaller
Eigenvalue decomposition (EVD)
rank. Simulation results obtained confirm the superiority of the proposed Krylov low-
Krylov subspace
rank channel esti