Prediction of fast fading channel using support vector

Due to channel exists strange attractors, the paper proposed SV predictive model of multi-path fading channel based on the origin of support vector (SV) concept. According to the chaotic reconstructing theory of phase space delay, the chaotic fading channel model was established. The training set is used to be support object elements. Machine self-learning makes error least upper bound of generalization model to be minimum. The non-linear higher dimension map was realized by the least squares support vector domain. The result indicates that the support vector domain needs little support vector with fast convergence rate. The system has robustness characteristic and kernel function of flexible choice.