Blind Signal Separation for Digital Communication Data

Abstract : Blind source separation, often called independent component analysis , is a main field of research in signal processing since the eightees. It consists in retrieving the components, up to certain indeterminacies, of a mixture involving statistically independent signals. Solid theoretical results are known; besides, they have given rise to performent algorithms. There are numerous applications of blind source separation. In this contribution, we particularize the separation of telecommunication sources. In this context, the sources stem from telecommunication devices transmitting at the same time in a given band of frequencies. The received data is a mixed version of all these sources. The aim of the receiver is to isolate (separate) the different contributions prior to estimating the unknown parameters associated with a transmitter. The context of telecommunication signals has the particularity that the sources are not stationary but cyclo-stationary. Now, in general, the standard methods of blind source separation assume the stationarity of the sources. In this contribution , we hence make a survey of the well-known methods and show how the results extend to cyclo-stationary sources.
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Chapitre d'ouvrage
Rama Chellappa, Sergios Theodoridis. Academic Press Library in Signal Processing, Academic Press, pp.135-186, 2013, 978-0123965004. 〈10.1016/B978-0-12-396500-4.00004-1〉
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Antoine Chevreuil, Philippe Loubaton. Blind Signal Separation for Digital Communication Data. Rama Chellappa, Sergios Theodoridis. Academic Press Library in Signal Processing, Academic Press, pp.135-186, 2013, 978-0123965004. 〈10.1016/B978-0-12-396500-4.00004-1〉. 〈hal-00790078〉

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