Deterministic Blind Separation of Sources having Different Symbol Rates using Tensor-Based Parallel Deflation

André L. F. de Almeida (1) , Pierre Comon (2) , Xavier Luciani (2, 3)

1 GTEL - Wireless Telecom Research Group [Fortaleza]
2 Laboratoire d'Informatique, Signaux, et Systèmes de Sophia-Antipolis (I3S) / Equipe SIGNAL
3 LTSI - Laboratoire Traitement du Signal et de l'Image

We address the problem of blind separation of non-synchronous statistically independent sources from underdetermined mixtures. A deterministic tensor-based receiver exploiting symbol rate diversity by means of parallel deflation is proposed. By resorting to bank of samplers at each sensor output, a set of third-order tensors is built, each one associated with a different source symbol period. By applying multiple Canonical Decompositions (CanD) on these tensors, we can obtain parallel estimates of the related sources along with an estimate of the mixture matrix. Numerical results illustrate the bit-error-rate performance of the proposed approach for some system configurations.

Mots clés: Blind source separation; underdetermined mixtures; tensor decomposition; non-synchronous sources; parallel deflation

Domaines: Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

André L. F. de Almeida, Pierre Comon, Xavier Luciani. Deterministic Blind Separation of Sources having Different Symbol Rates using Tensor-Based Parallel Deflation. Ninth International Conference on Latent Variable Analysis and Signal Separation, Sep 2010, Saint Malo, France. pp.362-369. ⟨hal-00540504⟩