By Topic

Blind equalization via the use of generalized pattern search optimization and zero forcing sectionnally convex cost function

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
A. Zaouche ; Institute of Electronics Microelectronics and Nanotechnology IEMN - UMR CNRS 8520; D.O.A.E- University of Valencienes, Le Mont Houy, 59313, Cedex 9 -France- ; I. Dayoub ; J. M. Rouvaen

The present paper deals with the formulation of the baud spaced blind equalization in the presence of Gaussian noise as an unconstrained optimization problem via the use of generalized pattern search (GPS) algorithm and sectionally convex blind cost function. Simulation results show that the proposed approach is much more likely to outperform the classical CMA in terms of minimum square error (MSE) and inter-symbol interference (ISI) quantities, however the global convergence is not warranted for baud spaced blind equalization

Published in:

2006 2nd International Conference on Information & Communication Technologies  (Volume:2 )

Date of Conference:

0-0 0