Blind Modulation Classification for Cognitive Satellite in the Spectral Coexistence Context

Vincent Gouldieff (1, 2, 3) , Jacques Palicot (1, 2) , Steredenn Daumont (3)

1 IETR - Institut d'Électronique et des Technologies du numéRique
2 SCEE - Signal, Communication et Electronique Embarquée
3 Zodiac Data Systems

The scarcity of the usable satellite spectrum has led to a need for advanced communication techniques. Among them, multi-satellite networks have been promoted for their ability to reuse the frequency bands in a more aggressive manner. This is made possible by sharing both the spectral and spatial degrees of freedom. Meanwhile, the concept of Cognitive Satellite (CS) was deeply investigated to make the best of these novel architectures. In this context, very few blind signal processing methods were proposed to tackle the co-channel interference issues entailed by such systems. Herein, we develop a novel low-complexity algorithm for blind Automatic Modulation Classification (AMC) and parameters estimation in the strongly interfering scenario. The proposed method rely on an Analytical study of the Mth-Power non-linear Transformation (AMPT) of the co-channel mixture. Theoretical analysis and extensive simulations show the effectiveness of the proposed method in various scenarios.

Mots clés: Blind Signal Processing; Cognitive Satellite; Coexistence Scenario; Automatic Modulation Classification; Mth-Power nonlinear Transformation

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

Vincent Gouldieff, Jacques Palicot, Steredenn Daumont. Blind Modulation Classification for Cognitive Satellite in the Spectral Coexistence Context. IEEE Transactions on Signal Processing, 2017, 65 (12), pp.3204-3217. ⟨10.1109/TSP.2017.2688976⟩. ⟨hal-01513362⟩