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A nonlinear channel estimator using complex Least Square Support VectorMachines (LS-SVM) is proposed for pilot-aided OFDM system and applied to LongTerm Evolution (LTE) downlink under high mobility conditions. The estimationalgorithm makes use of the reference signals to estimate the total frequencyresponse of the highly selective multipath channel in the presence ofnon-Gaussian impulse noise interfering with pilot signals. Thus, the algorithmmaps trained data into a high dimensional feature space and uses the structuralrisk minimization (SRM) principle to carry out the regression estimation forthe frequency response function of the highly selective channel. Thesimulations show the effectiveness of the proposed method which has goodperformance and high precision to track the variations of the fading channelscompared to the conventional LS method and it is robust at high speed mobility.

Nonlinear Channel Estimation for OFDM System by Complex LS-SVM under High Mobility Conditions