A blind MIMO channel estimation method robust to order overestimation
Signal Processing - Special issue on independent components analysis and beyond
A signal perturbation free whitening-rotation-based semiblind approach for MIMO channel estimation
IEEE Transactions on Signal Processing
Blind adaptive equalization of MIMO systems: new recursive algorithms and convergence analysis
IEEE Transactions on Circuits and Systems Part I: Regular Papers
A signal-perturbation-free transmit scheme for MIMO-OFDM channel estimation
IEEE Transactions on Circuits and Systems Part I: Regular Papers
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Blind channel estimation and blind minimum mean square error (MMSE) equalization of multiple-input multiple-output (MIMO) communications channels arising in multiuser systems is considered, using primarily the second-order statistics of the data. The basis of the approach is the design of multiple zero-forcing equalizers that whiten the noise-free data at multiple delays. In the past such an approach has been considered using just one zero-forcing equalizer at zero-delay. Infinite impulse response (IIR) channels are allowed. Moreover, the multichannel transfer function need not be column-reduced. The proposed approach also works when the “subchannel” transfer functions have common zeros so long as the common zeros are minimum-phase zeros. The channel length or model orders need not be known. Using second-order statistics, the sources are recovered up to a unitary mixing matrix, and are further “unmixed” using higher order statistics of the data. Two illustrative simulation examples are provided where the proposed method is compared with its predecessors and an existing method to show its efficacy