Comparative performance analysis of eight blind source separation methods on radiocommunications signals

For about two decades, many second order (SO) and fourth order (FO) blind methods have been developed to separate overdetermined mixtures of statistically independent narrowband (NB) sources. Besides, mainly to overcome some limitations of these methods, sixth order methods have been developed. Nevertheless, despite of this great number of methods, the performance of the latter for arbitrary electromagnetic sources are still almost unknown, which limits their use in operational contexts. The purpose of this paper is to fill the gap previously mentioned by presenting a comparative performance analysis of eight blind source separation (BSS) methods for arbitrary overdetermined mixtures of sources borrowed from the radiocommunications context, and to show off both the advantages and the drawbacks of these methods.

[1]  Pierre Comon,et al.  From source separation to blind equalization, contrast-based approaches , 2001 .

[2]  J. Cardoso,et al.  Blind beamforming for non-gaussian signals , 1993 .

[3]  P. Comon,et al.  Blind Identification of Overcomplete MixturEs of sources (BIOME) , 2004 .

[4]  Pascal Chevalier,et al.  Optimal separation of independent narrow-band sources: Concept and performance , 1999, Signal Process..

[5]  Anne Ferréol,et al.  Correction to "On the behavior of current second and higher order blind source separation methods for cyclostationary sources" , 2002, IEEE Trans. Signal Process..

[6]  Pierre Comon,et al.  Independent component analysis, A new concept? , 1994, Signal Process..

[7]  P. McCullagh Tensor Methods in Statistics , 1987 .

[8]  Laurent Albera,et al.  Fourth order blind identification of underdetermined mixtures of sources (FOBIUM) , 2003, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)..

[9]  Laurent Albera,et al.  Higher order blind separation of non zero-mean cyclostationary sources , 2002, 2002 11th European Signal Processing Conference.

[10]  Aapo Hyvärinen,et al.  A Fast Fixed-Point Algorithm for Independent Component Analysis of Complex Valued Signals , 2000, Int. J. Neural Syst..

[11]  Laurent Albera,et al.  SIXTH ORDER BLIND IDENTIFICATION OF UNDERDETERMINED MIXTURES (BIRTH) OF SOURCES , 2003 .

[12]  Eric Moulines,et al.  A blind source separation technique using second-order statistics , 1997, IEEE Trans. Signal Process..

[13]  Laurent Albera,et al.  Fourth-order blind identification of underdetermined mixtures of sources (FOBIUM) , 2005, IEEE Transactions on Signal Processing.

[14]  Randy L. Haupt,et al.  Introduction to Adaptive Arrays , 1980 .

[15]  Anne Ferréol,et al.  On the behavior of current second and higher order blind source separation methods for cyclostationary sources , 2000, IEEE Trans. Signal Process..

[16]  Laurent Albera,et al.  ICAR: independent component analysis using redundancies , 2004, 2004 IEEE International Symposium on Circuits and Systems (IEEE Cat. No.04CH37512).

[17]  Pascal Chevalier,et al.  On the blind implementation of the ultimate source separators for arbitrary noisy mixtures , 1999, Signal Process..