Title :
Efficient PA modeling using neural network and measurement setup for memory effect characterization in the power device
Author :
Ahmed, Arif ; Srinidhi, E.R. ; Kompa, G.
Author_Institution :
Fachgebiet Hochfrequenztechnik, Kassel Univ., Germany
Abstract :
This paper proposes an artificial neural network (ANN) model for power amplifiers (PAs), which exhibits memory effects. This model is based on a complex-valued multi-layered perceptron (MLP) time delay neural network (TDNN). The developed PA models are based on TDNN with unity and nonuniform time delay taps between instantaneous and previous input signal of the PA. Modeling results for both types of PA models are compared to show the advantage of the newly developed model. Furthermore, a measurement setup for analyzing and measuring the nonlinearity and memory effects in GaN active power device is also proposed.
Keywords :
III-V semiconductors; circuit analysis computing; circuit optimisation; delays; gallium compounds; multilayer perceptrons; power amplifiers; GaN; active power device; artificial neural networks; complex-valued multi-layered perceptrons; memory effect characterization; nonlinearity effects; power amplifier modeling; time delay neural networks; time lay taps; Artificial neural networks; Delay effects; Frequency; Intelligent networks; Mathematical model; Neural networks; Nonlinear dynamical systems; Power amplifiers; Power measurement; Power system modeling;
Conference_Titel :
Microwave Symposium Digest, 2005 IEEE MTT-S International
Print_ISBN :
0-7803-8845-3
DOI :
10.1109/MWSYM.2005.1516632