lab-emi/OpenDPD
OpenDPD is an end-to-end learning framework built in PyTorch for power amplifier (PA) modeling and digital pre-distortion (DPD). You are cordially invited to contribute to this project by providing your own backbone neural networks, pretrained models or measured PA datasets.
This project helps RF engineers and researchers improve the efficiency and signal quality of power amplifiers (PAs) in wireless communication systems. It takes raw baseband signal data from digital transmitters and uses machine learning to create a 'digital pre-distortion' (DPD) model. The output is a highly optimized DPD model that can be used to compensate for PA imperfections, along with detailed visualizations and performance metrics of the trained model.
124 stars.
Use this if you are an RF engineer or researcher working on wireless communication systems and need to accurately model power amplifiers or implement digital pre-distortion to improve signal fidelity and power efficiency.
Not ideal if you are not involved in radio frequency engineering or do not work with power amplifier characterization and linearization.
Stars
124
Forks
29
Language
Python
License
Apache-2.0
Category
Last pushed
Feb 15, 2026
Commits (30d)
0
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