Modélisation et estimation de canaux de communication non linéaires à l'aide d'un modèle de Volterra-Parafac passe-bande et d'un filtre de Kalman étendu
Résumé
Discrete bandpass complex Volterra models are very useful for modeling nonlinear communication channels as those encountered in satellite communication systems and in radio over fiber wireless communication networks, the nonlinearities being introduced by power amplifiers, on the one hand, and electrical-optical conversion, on the other hand. These Volterra models present the specificity to include only odd-order nonlinear terms, with kernels characterized by a double symmetry. The main drawback of these models is their parametric complexity. In this paper, we develop a new class of Volterra models, called bandpass Volterra-Parafac models, with a reduced parametric complexity, by using a doubly symmetric Parafac decomposition of the Volterra kernels. An adaptive algorithm based on an extended Kalman filter is then proposed for estimating the parameters of these models. Some Monte Carlo simulation results are presented to illustrate the performance of the proposed estimation algorithm, in the case of cubic complex Volterra systems excited by PSK input signals.