Predistortion of Nonlinear High-Power Amplifiers Using Neural Networks

摘要：

This paper presents a new predistortion scheme based on Radial Basis Function (RBF) neural network for high-power amplifier (HPA) with memory in an orthogonal frequency division multiplexing (OFDM) system.An efficient algorithm to update the neural network weights parameters and the centers and widths of RBF is derived.Simulation results show that the proposed neural network predistorter can effectively reduce the bit error rate and adjacent channel interference caused by nonlinear HPA and produce a faster convergence speed than the conventional backpropagation algorithm.

作者: Jiantao Yang Jun Gao Xiaotao Deng Ming Yang

作者单位: Dept of Communication Engineering,Naval University of Engineering,Wuhan,China

会议类型: 国际会议

会议名称: 9th International Conference on Signal Processing(第九届国际信号处理学术会议)(ICSP08)

会议地点: 北京

会议语种:英文

在线出版日期: 2008-10-26（万方平台首次上网日期，不代表论文的发表时间）