A quadratic complexity eigenspace technique for blind SIMO channel identification

Houcem Gazzah (1) , Jean-Pierre Delmas (2, 3, 4, 5)

1 Department of Electrical and Computer Engineering (University of Sharjah)
2 TIPIC-SAMOVAR - Traitement de l'Information Pour Images et Communications
3 TSP - CITI - Communications, Images et Traitement de l'Information
4 SAMOVAR - Services répartis, Architectures, MOdélisation, Validation, Administration des Réseaux
5 CNRS - Centre National de la Recherche Scientifique

Eigenspace techniques are very popular techniques for blind channel identification, but are ones with a large complexity, cubic in the channel order. The newly introduced channel compaction is a signal processing technique that consists in using small-sized linear transformations to progressively force to zero some of the channel coefficients. As such, channel compaction was used to develop the first (and, up to now, the only) blind channel equalization technique with a quadratic complexity. In this paper, we apply blind compaction to develop a new blind identification technique, the first to have a quadratic complexity. Simulation tests show that the low-complexity compaction-based blind identification performs quite similarly to the most referenced existing eigenspace blind identification techniques

Mots clés: Blind SIMO channel identification; Quadratic complexity eigenspace

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

Houcem Gazzah, Jean-Pierre Delmas. A quadratic complexity eigenspace technique for blind SIMO channel identification. ISSSE 2012 : International Symposium on Signals, Systems and Electronics, Oct 2012, Potsdam, Germany. pp.1 - 5, ⟨10.1109/ISSSE.2012.6374337⟩. ⟨hal-01299280⟩