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

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.