Improved super-exponential algorithm for blind equalization
Digital Signal Processing
An iterative equalization method for nonirreducible MIMO FIR channels
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Blind adaptive equalization of MIMO systems: new recursive algorithms and convergence analysis
IEEE Transactions on Circuits and Systems Part I: Regular Papers
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This article presents a new subspace based method for blind identification of a p-input/q-output system, where q>p. This method exploits a minimum noise subspace (MNS) to retrieve the system impulse responses. The MNS method requires only q-p noise vectors as opposed to all noise vectors needed by a standard subspace (SS) method. It is shown that the MNS can be obtained in a parallel structure from a set of tuples (combinations) of system outputs that form a properly connected sequence (PCS). The PCS exploits with minimum redundancy the diversity among system outputs. The MNS method is much more efficient in computation than the SS method, although the former is less robust to noise than the latter