Electronic Science and Technology ›› 2020, Vol. 33 ›› Issue (2): 20-24.doi: 10.16180/j.cnki.issn1007-7820.2020.02.004

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Behavior Modeling of Class-D Power Amplifier Based on Encoder-Decoder Model

ZHAO Yihe,SHAO Jie,CHENG Yongliang   

  1. School of Electronic Information Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China
  • Received:2019-01-10 Online:2020-02-15 Published:2020-03-12
  • Supported by:
    Nation Natural Foundation of China(61401198)


Class D power amplifiers have excellent transmission efficiency and are classified as power amplifiers. Their output signals have large nonlinear distortion. The behavior modeling of calss-D power amplifier should take into account both nonlinearity and memory characteristics. This study introduced wavelet transform into the encoder-decoder neural network model, and proposed sequence to sequence wavelet neural network model. In this paper, the encoder-decoder model and sequence to sequence wavelet model based on gated recurrent unit were used in the behavior modeling of class-D power amplifier. Experiments results demonstrated that the proposed behavior model of class-D power amplifier had higher precision in time and frequency domain than the traditional Voterra-Laguerre model.

Key words: class-D power amplifier, nonlinearsystem, behaviormodeling, gated recurrent unit, encoder-decoder neural network, wavelet transform

CLC Number: 

  • TP274