Computer Science – Learning
Scientific paper
2011-08-31
International Journal of Wireless & Mobile Networks (IJWMN) Vol. 3, No. 4, August 2011
Computer Science
Learning
11 pages
Scientific paper
10.5121/ijwmn.2011.3412
A nonlinear channel estimator using complex Least Square Support Vector Machines (LS-SVM) is proposed for pilot-aided OFDM system and applied to Long Term Evolution (LTE) downlink under high mobility conditions. The estimation algorithm makes use of the reference signals to estimate the total frequency response of the highly selective multipath channel in the presence of non-Gaussian impulse noise interfering with pilot signals. Thus, the algorithm maps trained data into a high dimensional feature space and uses the structural risk minimization (SRM) principle to carry out the regression estimation for the frequency response function of the highly selective channel. The simulations show the effectiveness of the proposed method which has good performance and high precision to track the variations of the fading channels compared to the conventional LS method and it is robust at high speed mobility.
Charrada Anis
Samet Abdelaziz
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