Study and Simulation of RF Power Amplifier Behavioral Model Based on RBF Neural Network

摘要：

Modeling power amplifier is a key step for designing power amplifying system and predistortion system. Whether nonlinearity and memory effects of power amplifier can be modeled correctly or not, has an important impact on system simulation performance. This paper presented and analyzed the Radial Basis Functions Neural Network (RJBFNN), Utilizing input and output data extracted from Freescale semiconductor transistor MRF6S21140 model and designed circuit in ADS circumstance, simulate two kinds of Back Propagation Neural Network(BPNN) models and RBFNN models, and compute the error. Simulation results show that the proposed RBFNN behavioral model has less modeling error, and output waveform of the model can be more close to real waveform. The model can be set up in ADS and can be applied for systemlevel simulation, system simulation performance can be more close to real system, and has a significant sense for designing real system.

作者: Jiuchao Li Jingchang Nan Jingmei Zhao

作者单位: College of electrics and information engineering, Liaoning Technical University,Huludao, 125105, China

会议类型: 国际会议

会议名称: 2010 International Conference on Microwave and Millimeter Wave Technology(2010国际微波与毫米波技术会议 ICMMT2010)

会议地点: 成都

会议语种:英文

页码: 1465-1467

在线出版日期: 2010-05-08（万方平台首次上网日期，不代表论文的发表时间）