Blind separation of cyclostationary sources with common cyclic frequencies

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Abstract

We propose a new method for blind source separation of cyclostationary sources, whose cyclic frequencies are unknown and may share one or more common cyclic frequencies. The suggested method exploits the second-order cyclostationarity statistics of observation signals to build a set of matrices which has a particular algebraic structure. We also introduce an automatic point selection procedure for the determination of these matrices to be joint diagonalized in order to identify the mixing matrix and recover the source signals as a result. The nonunitary joint diagonalization is ensured by Broyden-Fletcher-GoldfarbShanno (BFGS) method which is the most commonly used update strategy for implementing a quasi-newton technique. Numerical simulations are provided to demonstrate the usefulness of the proposed method in the context of digital communications and to compare it with another method based upon an unitary joint diagonalization algorithm.

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Brahmi, A., Ghennioui, H., Corbier, C., Lahbabi, M., & Guillet, F. (2017). Blind separation of cyclostationary sources with common cyclic frequencies. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10169 LNCS, pp. 449–458). Springer Verlag. https://doi.org/10.1007/978-3-319-53547-0_42

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