NDLI: Un algorithme Quasi-Newton dans le domaine fréquentiel pour l'égalisation de transmission en salves

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Un algorithme Quasi-Newton dans le domaine fréquentiel pour l'égalisation de transmission en salves

Content Provider	Semantic Scholar
Author	Berberidis, Kostas Rantos, Stelios Palicot, Jacques
Copyright Year	2001
Abstract	Resume Dans ce papier, nous proposons un nouveau type d’egaliseur qui appartient a la famille des algorithmes Quasi-Newton (QN).Nous presentons un Egaliseur Lineaire Transverse et un Egaliseur a Retour de Decisions. Dans le premier cas, le Hessien est approche par un developpement en serie de matrices de Toeplitz. Cette formulation nous permet de developper un algorithme performant dans le domaine frequentiel (DF). Cette meme approche est utilisee pour l’algorithme d’adaptation du filtre direct de l’ERD. L’algorithme obtenu ainsi offre a la fois les avantages de vitesse de convergence des algorithmes QN et de moindre complexite due a la formulation dans le DF. Abstract – In this paper two new adaptive equalizers are proposed which belong to the Quasi-Newton(QN) algorithmic family. The first equalizer is a Linear Transversal Equalizer (LTE) and the second is a Decision Feedback Equalizer (DFE).In the LE case the involved inverse Hessian matrix is approximated by a proper expansion consisting of the powers of a Toeplitz matrix. Due to this formulation the algorithm can be efficiently implemented in the transform domain(TD) using FFT. The same idea is applied to the Feedforward part of the DFE. The derived algorithms exhibit faster convergence (advantage of QN algorithm) and less complexity as compared to other Newton type algorithms (implementation in the TD).
File Format	PDF HTM / HTML
Alternate Webpage(s)	http://documents.irevues.inist.fr/bitstream/handle/2042/13353/PAPER213.pdf;jsessionid=58C2D46FC1DC5D65CA57CC1024C08A9B?sequence=1
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article

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