Millimeter-wave modeling based on transformer model for InP high electron mobility transistor

In this paper，the small-signal modeling of the Indium Phosphide High Electron Mobility Transistor （InP HEMT）based on the Transformer neural network model is investigated. The AC S-parameters of the HEMT device are trained and validated using the Transformer model. In the proposed model，the eight-layer transformer encoders are connected in series and the encoder layer of each Transformer consists of the multi-head attention lay⁃ er and the feed-forward neural network layer. The experimental results show that the measured and modeled S-pa⁃ rameters of the HEMT device match well in the frequency range of 0. 5-40 GHz，with the errors versus frequency less than 1%. Compared with other models，good accuracy can be achieved to verify the effectiveness of the pro⁃ posed model.