Transfer Learning with Transformer and LSTM for Digital Pre-distortion of Terahertz/mmWave Transceiver

To ensure high-quality communication, it’s of great value to use digital pre-distortion (DPD) to linearize the core component power amplifier (PA) of terahertz/mmWave transceiver. In this work, we propose transfer learning with Transformer and LSTM for DPD of terahertz/mmWave transceiver, which uses Transformer based PA behavioral model to train effective and lightweight LSTM model for DPD. To collect and analyze the signal data of terahertz/mmWave transceiver, we set up a physical platform for the D-band system. Through experiments, we show that the proposed method is capable of significantly reducing in-band and out-band distortion while avoiding the excessive complexity of DPD models.