NONLINEAR COMPENSATION BY SUPPORT VECTOR MACHINE APPROACH
NONLINEAR COMPENSATION BY SUPPORT VECTOR MACHINE APPROACH
复制标题
支持向量机方法的非线性补偿
DOI：
10.5687/sss.2002.176
复制
发表时间：
2002
期刊：
影响因子：
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通讯作者：
A. Sano
中科院分区：
文献类型：
--
作者：
T. Eda;Yuanming Ding;A. Sano
提出了一种基于数据库的支持向量回归（SVR）自适应预失真方法，用于补偿高功率放大器（HPA）中未知的线性和非线性失真。该方法可以通过输入输出数据样本的学习过程来构造非线性HPA的逆模型。为了减少批处理优化的计算量，给出了一种在线自适应更新8VR机参数的算法。通过与普通的查表方案进行比较，结果表明，所提出的基于数据的方法可以获得改善的抑制功率谱的放大器输出的输入频带以外的非线性失真所造成的。
A new adaptive predistortion method for compensation of unknown linear and nonlinear distortion in a high power amplifier (HPA) is investigated by a databased approach using the support vector regression (SVR). The proposed approach can construct an inverse model of the nonlinear HPA by learning procedure using training input-output data samples. An online adaptive algorithm for updating the parameters of the 8VR machines is also given to reduce the computational burden of the batch processed optimization. By comparing with an ordinary look-up table scheme, it is shown that the proposed data-based approach can attain improved suppression of the power spectrum of the amplifier output outside the input frequency band caused by the nonlinear distortions.