DocumentCode
1343966
Title
Stationary points of a kurtosis maximization algorithm for blind signal separation and antenna beamforming
Author
Ding, Zhi ; Nguyen, Tuan
Author_Institution
Dept. of Electr. & Comput. Eng., Iowa Univ., Iowa City, IA, USA
Volume
48
Issue
6
fYear
2000
fDate
6/1/2000 12:00:00 AM
Firstpage
1587
Lastpage
1596
Abstract
Blind source separation has been the subject of extensive research. In particular, blind antenna beamforming is an effective signal separation technique for communication systems to combat co-channel interference. Among many potential candidate approaches, the simple constant modulus algorithm (CMA) has been widely studied and used in practice. The CMA is designed to capture and separate signals with negative kurtosis. However, when some signals have positive kurtoses, the CMA is unable to capture and separate these sources. We show that the kurtosis maximum algorithm (KMA) can capture signals with both the positive and negative kurtoses. Its global convergence proof is presented for noiseless systems with multiple signals sources and for systems with a single source and zero-kurtosis (such as Gaussian) additive noise
Keywords
Gaussian noise; array signal processing; cochannel interference; convergence of numerical methods; higher order statistics; interference suppression; optimisation; CMA; Gaussian additive noise; blind antenna beamforming; blind signal separation; blind source separation; co-channel interference; communication systems; constant modulus algorithm; fourth-order cumulant; global convergence; kurtosis maximization algorithm; multiple signals sources; negative kurtosis; noiseless systems; positive kurtosis; single source system; stationary points; zero-kurtosis additive noise; Additive noise; Array signal processing; Blind source separation; Convergence; Gaussian noise; Interchannel interference; Signal design; Signal processing; Signal processing algorithms; Source separation;
fLanguage
English
Journal_Title
Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
1053-587X
Type
jour
DOI
10.1109/78.845917
Filename
845917
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