Title :
A super-exponential algorithm for blind deconvolution of MIMO system
Author :
Yeung, Ka Lok ; Yau, Sze Fong
Author_Institution :
Dept. of Electr. & Electron. Eng., Hong Kong Univ. of Sci. & Technol., Kowloon, Hong Kong
Abstract :
In this paper, a method for MIMO blind deconvolution is proposed. The method is applicable to the case of non-Gaussian i.i.d. input signals. The core of the method is an algorithm which extracts one of the input signals from the information of the output signals only. This algorithm is an non-trivial generalization of the Shalvi-Weinstein algorithm for SISO blind deconvolution and converges in super-exponential rate possibly after finite iterations. By recursive use of this algorithm, extraction of all input signals can be achieved
Keywords :
MIMO systems; convergence of numerical methods; deconvolution; MIMO system; Shalvi-Weinstein algorithm; blind deconvolution; convergence; nonGaussian i.i.d. input signal extraction; recursive iterative method; super-exponential algorithm; Convolution; Data communication; Data mining; Deconvolution; Finite impulse response filter; Higher order statistics; Image restoration; MIMO; Stochastic systems; Wireless communication;
Conference_Titel :
Circuits and Systems, 1997. ISCAS '97., Proceedings of 1997 IEEE International Symposium on
Print_ISBN :
0-7803-3583-X
DOI :
10.1109/ISCAS.1997.612836
