Perturbation analysis for subspace decomposition with applications in subspace-based algorithms
IEEE Transactions on Signal Processing
Training-based and semiblind channel estimation for MIMO systems with maximum ratio transmission
IEEE Transactions on Signal Processing
A semi-blind channel estimation method for multiuser multiantenna OFDM systems
IEEE Transactions on Signal Processing
On the performance of semi-blind subspace-based channel estimation
IEEE Transactions on Signal Processing
Whitening-rotation-based semi-blind MIMO channel estimation
IEEE Transactions on Signal Processing
Optimal training design for MIMO OFDM systems in mobile wireless channels
IEEE Transactions on Signal Processing
A Semiblind Channel Estimation Approach for MIMO–OFDM Systems
IEEE Transactions on Signal Processing - Part I
On the second-order statistics of the weighted sample covariance matrix
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
On the second-order statistics of the eigenvectors of samplecovariance matrices
IEEE Transactions on Signal Processing
Subspace approach to blind and semi-blind channel estimation for space-time block codes
IEEE Transactions on Wireless Communications
Optimal training for MIMO frequency-selective fading channels
IEEE Transactions on Wireless Communications
Blind estimation and equalization of MIMO channels via multidelay whitening
IEEE Journal on Selected Areas in Communications
A signal-perturbation-free transmit scheme for MIMO-OFDM channel estimation
IEEE Transactions on Circuits and Systems Part I: Regular Papers
Hi-index | 35.68 |
It was shown in our previous work that, in the noise-free case, the whitening-rotation (WR)-based MIMO channel estimation algorithm is subject to a signal perturbation error, justifying that the WR-based method is efficient only in the low signal-to-noise ratio (SNR) case. In this paper, a very efficient signal-perturbation-free WR-based approach is proposed for semiblind channel estimation of MIMO systems. A novel transmit scheme is developed based on the eigenvalue decomposition of the correlation matrix of the transmitted signal. The new scheme is to send a small volume of data bearing the information of the correlation matrix to the receiver for the cancellation of the signal perturbation error so as to improve the performance of the WR-based method in the case of high SNRs. Then, a perturbation analysis of the proposed WR-based semiblind method with the new transmit scheme is conducted, leading to a closed-form expression for the mean square error (MSE) of the channel estimate. Computer simulations show that the proposed approach significantly outperforms the original WR-based method as well as some other channel estimation methods for all SNR levels.