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Extraction of a weak co-channel interfering communication signal using complex independent component analysis

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Author
Hagstette, Matthew E.
Date
2013-06
Advisor
Fargues, Monique P.
Cristi, Roberto
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Abstract
Independent Component Analysis (ICA) has largely been applied to the biomedical field over the past two decades and only recently extended to the processing of complex non-circular sources. The feasibility and performance of complex ICA to extract a weak co-channel interfering communications signal from a television broadcast signal is investigated in this thesis. The performance of three algorithms, complex maximization of non-Gaussianity (CMN) by Novey et al., RobustICA by Zarzoso et al., and complex fixed-point algorithm (CFPA) by Douglas, over varied interference-to-noise ratios (INR) for a fixed signal-to-interference ratio (SIR) is obtained by simulation. The communication signals examined for the weak interferer are binary phase-shift keying (BPSK), four-level rectangular quadrature amplitude modulation (4-QAM), and 16-level rectangular quadrature amplitude modulation (16-QAM), and the television broadcast signals are North American standard, Advanced Television Systems Committee (ATSC) and European standard, Digital Video Broadcasting - Terrestrial (DVB-T). Improved performance and sensitivity to the prewhitening step present in the ICA implementations are shown as the number of sensors increases.
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This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.
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http://hdl.handle.net/10945/34672
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