a krylov subspace based lowrank channel estimation in ofdm systems:ofdm系统中基于krylov子空间的低秩信道估计.pdf
ARTICLE IN PRESS Signal Processing 90 (2010) 1861–1872 Contents lists available at ScienceDirect Signal Processing journal homepage: 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
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