中文摘要：

为了提高OFDM系统的传输效率和提前获取移动信道信息，提出了一种新的非线性信道预测算法．首先利用重构嵌入相空间理论将支持向量机和非线性动力学理论联系起来，解决了训练数据的维数确定问题，为研究支持向量机提供了新的理论途径．在此基础上采用递归最小二乘支持向量机在高维空间中解决导频点的预测问题，最后在频域进行插值操作以估计其他频点处的信道参数．仿真结果表明，与传统的信道估计算法相比，在增加较小误码率的条件下，减少了导频个数，提高了系统的传输效率并提前获取了信道信息，为自适应技术的实施提供了重要的信息．

英文摘要：

To improve the transmission efficiency and obtain the information of channel in OFDM system, a novel nonlinear channel prediction algorithm is proposed. Firstly, Support Vector Machines were associated with nonlinear dynamics using the theory of reconstructed embedding phase space to determine the dimension of training data set, which provides a novel approach to investigate the Support Vector Machines. Then the prediction of pilot tones in time field was realized by Recurrent Least Squares Support Vector Machines （ RLS -SVM） in high dimensional space, and the interpolation operation was carried out in frequency field to estimate parameters of other tones. Simulation results show that the number of pilot tones is decreased at the same transmission rate and the transmission efficiency is improved under improvement of bit error rate. In addition, this method provides important Channel State Information （CSI） for realizing adaptive techniques.