Performance analysis of the subspace method for blind channel identification
Signal Processing - Special issue on subspace methods, part I: array signal processing and subspace computations
Blind identification of MIMO-FIR systems: a generalized linear prediction approach
Signal Processing - Special issue on blind source separation and multichannel deconvolution
Signal Processing Advances in Wireless and Mobile Communications, Volume 1: Trends in Channel Estimation and Equalization
Blind Channel Equalization and Identification
Blind Channel Equalization and Identification
A blind MIMO channel estimation method robust to order overestimation
Signal Processing - Special issue on independent components analysis and beyond
Subspace methods for the blind identification of multichannel FIRfilters
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Prediction error method for second-order blind identification
IEEE Transactions on Signal Processing
A blind multichannel identification algorithm robust to orderoverestimation
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Matrix outer-product decomposition method for blind multiplechannel identification
IEEE Transactions on Signal Processing
A subspace algorithm for certain blind identification problems
IEEE Transactions on Information Theory
A new blind estimation of MIMO channels based on HGA
AICI'11 Proceedings of the Third international conference on Artificial intelligence and computational intelligence - Volume Part II
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Many known second-order statistics (SOS)-based blind algorithms for MIMO channel estimation, including the subspace (SS) and linear prediction (LP) method, are sensitive to channel-order overestimations. To overcome this problem, an algorithm is proposed in [IEEE Trans. Signal processing 50(6) (2002) 1449-1458] for the SIMO system only, and then its simple generalization to the MIMO system is presented in [Signal Processing 84(2) (2004) 435-439]. In this paper, improvements and refinements on the algorithm in [Signal Processing 84(2) (2004) 435-439] are given, which makes the method robust to noise and round-off error. The method can give estimations of all channel impulse responses subject to a matrix ambiguity when only an upper bound for all MIMO channel orders is known. Simulations show that the algorithm is effective and robust.