NDLI: Multidimensional Blind Separation Using Higher-Order Statistics: Application to Non-Cooperative STBC Systems

Content Provider	Springer Nature Link
Author	Luo, Minggang Li, Liping Qian, Guobing Liao, Hongshu
Copyright Year	2014
Abstract	Blindly separating the intercepted signals is a challenging problem in non-cooperative multiple input multiple output systems in association with space–time block code (STBC) where channel state information and coding matrix are unavailable. To our knowledge, there is no report on dealing with this problem in literature. In this paper, the STBC systems are represented with an independent component analysis (ICA) model by merging the channel and coding matrices as virtual channel matrix. Analysis shows that the source signals are of group-wise independence and the condition of mutual independence can not be satisfied for ordinary ICA algorithms when specific modulations are employed. A new multidimensional ICA algorithm is proposed to separate the intercepted signals in this case by jointly block-diagonalizing (JBD) the cumulant matrices. In this paper, JBD is achieved by a 2-step optimization algorithm and a contrast function is derived from the JBD criterion to remove the additional permutation ambiguity with explicit mathematical explanations. The convergence of the new method is guaranteed. Compared with the ICA-based channel estimation methods, simulations show that the new algorithm, which does not introduce additional ambiguities, achieves better performance with faster convergence in a non-cooperative scenario.
Starting Page	2173
Ending Page	2192
Page Count	20
File Format	PDF
ISSN	0278081X
Journal	Circuits, Systems, and Signal Processing
Volume Number	33
Issue Number	7
e-ISSN	15315878
Language	English
Publisher	Springer US
Publisher Date	2014-01-23
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Non-cooperative STBC systems Higher-order statistics (HOS) Multidimensional independent component analysis (MICA) Blind separation Circuits and Systems Electrical Engineering Signal, Image and Speech Processing Electronics and Microelectronics, Instrumentation
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Signal Processing

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