Traditional blind identification methods for SIMO channels

such as subspace method (SS)

etc.

are based on the eigen value decomposition (EVD) or singular value decomposition (SVD) of the received signal's correlation matrix

which may need more data to make the estimation of correlation matrix be accurate.Recently a QR factorization based blind identification algorithm for SIMO channels with good performance and without calculating the correlation matrix is proposed.In this paper

we extend the QR factorization based algorithm for the blind identification of MIMO channels

and we then proved the extended algorithm to be valid for a more generalized case

that is

the source signals are spatially related.Simulations demonstrate that the QR-based identification algorithms for MIMO channels preserves advantages of fast convergence

low computational costs

and robustness to noise.We also compare the performance of the QR-based method with that of traditional MIMO blind identification algorithms.