MSc thesis project
AI-based Phase-Locked Loop (PLL) Calibration
Adapt learning-based calibration to phase-locked loop non-idealities.
This project aims to develop an AI-driven calibration system for phase-locked loop (PLL) non-idealities, such as jitter, phase noise, and locking instability, by adapting the OpenDPD framework, traditionally used for power amplifier linearization. Leveraging MATLAB for system-level PLL modeling and PyTorch for training neural networks, the project will automate the identification and compensation of non-linear behaviors in mixed-signal circuits. The deliverable: An open-source simulation package enabling AI-calibrated PLLs for high-precision communication systems.
Preferred Skills: MATLAB/Simulink, PyTorch, RF system fundamentals.
Contact Person: Dr. Masoud Babaie (M.Babaie@tudelft.nl) and Dr. Chang Gao (Chang.Gao@tudelft.nl)