CAJ | 학술논문

提出一种三层前馈输入延迟神经网络模型用于建立射频功率放大器有记忆的非线性行为模型.反向传播算法用来训练神经网络以提取神经网络模型参数.在仿真中,提出的模型可以通过典型的偶次多项式有记忆功率放大器模型来证明,并且比较了不同数目的延迟单元和隐层神经感知器的模型结构下的性能.为了用实验验证模型的有效性,建立了能达到60×106 sample/s采样率数字测试平台用于采集功率放大器的输入和输出数据.选用矢量信号源产生的3.75 MHz 16-QAM信号作为功放输入信号来测试功放的动态AM/AM和AM/PM特性.通过分析比较时域和频域仿真结果和实验测试结果,模型在收敛性、精度和执行效率方面都达到很好的效果.
제출일충삼층전궤수입연지신경망락모형용우건립사빈공솔방대기유기억적비선성행위모형.반향전파산법용래훈련신경망락이제취신경망락모형삼수.재방진중,제출적모형가이통과전형적우차다항식유기억공솔방대기모형래증명,병차비교료불동수목적연지단원화은층신경감지기적모형결구하적성능.위료용실험험증모형적유효성,건립료능체도60×106 sample/s채양솔수자측시평태용우채집공솔방대기적수입화수출수거.선용시량신호원산생적3.75 MHz 16-QAM신호작위공방수입신호래측시공방적동태AM/AM화AM/PM특성.통과분석비교시역화빈역방진결과화실험측시결과,모형재수렴성、정도화집행효솔방면도체도흔호적효과.
A novel behavioral model using three-layer time-delay feed-forward neural networks(TDFFNN)is adopted to model radio frequency(RF)power amplifiers exhibiting memory nonlinearities.In order to extract the parameters,the back-propagation algorithm is applied to train the proposed neural networks.The proposed model is verified by the typical odd-order-only memory polynomial model in simulation,and the performance is compared with different numbers of taped delay lines(TDLs)and perceptrons of the hidden layer.For validating the TDFFNN model by experiments,a digital test bench is set up to collect input and output data of power amplifiers at a 60×106 sample/s sampling rate.The 3.75 MHz 16-QAM signal generated in the vector signal generator(VSG)is chosen as the input signal,when measuring the dynamic AM/AM and AM/PM characteristics of power amplifiers.By comparisons and analyses,the presented model provides a good performance in convergence,accuracy and efficiency,which is approved by simulation results and experimental results in the time domain and frequency domain.