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Sensors 2012, 12(7), 9024-9045; doi:10.3390/s120709024
Article

Semi-Blind Signal Extraction for Communication Signals by Combining Independent Component Analysis and Spatial Constraints

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Received: 28 April 2012; in revised form: 15 June 2012 / Accepted: 28 June 2012 / Published: 2 July 2012
(This article belongs to the Section Physical Sensors)
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Abstract: Signal of interest (SOI) extraction is a vital issue in communication signal processing. In this paper, we propose two novel iterative algorithms for extracting SOIs from instantaneous mixtures, which explores the spatial constraint corresponding to the Directions of Arrival (DOAs) of the SOIs as a priori information into the constrained Independent Component Analysis (cICA) framework. The first algorithm utilizes the spatial constraint to form a new constrained optimization problem under the previous cICA framework which requires various user parameters, i.e., Lagrange parameter and threshold measuring the accuracy degree of the spatial constraint, while the second algorithm incorporates the spatial constraints to select specific initialization of extracting vectors. The major difference between the two novel algorithms is that the former incorporates the prior information into the learning process of the iterative algorithm and the latter utilizes the prior information to select the specific initialization vector. Therefore, no extra parameters are necessary in the learning process, which makes the algorithm simpler and more reliable and helps to improve the speed of extraction. Meanwhile, the convergence condition for the spatial constraints is analyzed. Compared with the conventional techniques, i.e., MVDR, numerical simulation results demonstrate the effectiveness, robustness and higher performance of the proposed algorithms.
Keywords: independent component analysis (ICA); constrained ICA; signal extraction; spatial constraint; initialization independent component analysis (ICA); constrained ICA; signal extraction; spatial constraint; initialization
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Wang, X.; Huang, Z.; Zhou, Y. Semi-Blind Signal Extraction for Communication Signals by Combining Independent Component Analysis and Spatial Constraints. Sensors 2012, 12, 9024-9045.

AMA Style

Wang X, Huang Z, Zhou Y. Semi-Blind Signal Extraction for Communication Signals by Combining Independent Component Analysis and Spatial Constraints. Sensors. 2012; 12(7):9024-9045.

Chicago/Turabian Style

Wang, Xiang; Huang, Zhitao; Zhou, Yiyu. 2012. "Semi-Blind Signal Extraction for Communication Signals by Combining Independent Component Analysis and Spatial Constraints." Sensors 12, no. 7: 9024-9045.


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