1 IWS-IEEE.org Visit: Behavioral Modeling of Power Amplifier with Long Term Memory Effects using Recurrent Neural Networks Chuan Zhang, Shuxia Yan, Qi-Jun Zhang, Jian-Guo Ma WE1B-5 School of Electronics and Information Engeering Tianjin University, China 2 Outline 1. Background 2. Recurrent neural network technique for PA 3. A PA example modeled by RNN and DNN 4. Conclusion 1. Background 4 ANN modeling technique ANN can represent multi-dimensional nonlinear input-output problems ANN model is fast and compact ANN becomes a logical choice as a basic part in an automated modeling algorithm 5 Software support Training data Power Amplifiers Agilent ADS NeuroModeler Agilent ADS Circuit/ System Simulation/ Optimization Fast behavior models 6 PA example 7 Behavioral modeling of PA 1. Dynamic neural network (DNN) 2. Recurrent neural network (RNN) 8 DNN for modeling Short-term memory effect Short-term memory effect DNN Vin Vout 9 DNN for modeling Short-term memory effect 10 DNN for modeling long-term memory effect Long-term memory effect DNN VinVin_LVout_L Vout 11 Slow-changing signals 12 DNN for modeling long-term memory effect 13 Gain comparison between DNN model and original circuit 14 IMD3 comparison between DNN long- term model and original circuit 2. Recurrent neural network (RNN) 16 RNN for modeling Short-term memory effect Short-term memory effect RNN Vin Vout 17 RNN for modeling Short-term memory effect V in (t-)V in (t-2)V out (t-) V out (t-2) 18 RNN for modeling long-term memory effect Long-term memory effect RNN VinVin_LVout_L Vout 19 RNN for modeling long-term memory effect =k* 20 Equivalent circuit of the RNN model 3. A PA example modeled by RNN and DNN 22 My PA example modeled by RNN and DNN 23 Table comparison with DNN and RNN 24 Gain comparison between DNN model,RNN model and original circuit 25 IMD3 comparison between DNN model,RNN model and original circuit 4. Conclusion 27 Conclusion We have presented an RNN method for modeling nonlinear PA circuit with memory effects. By including new slow changing signals extracted from the PA input and output signals, the proposed formulation of RNN can effectively represent long term memory effects. Thank you !