Classical and Quantum Signal Processing Research Lab

Projects

– Automatic Modulation Recognition (AMR) Based on Subspace and Machine Learning for Harmonically Modulated (HM) Signals, supported by TÜBİTAK (1002-A Programme):
This project investigates the effects of nonlinear phase transformations and spectral distortions introduced by harmonic modulation on automatic modulation recognition systems. The study combines simulation-based analyses with experimental validation in a real RF environment using software-defined radio platforms, including ADALM-Pluto SDR, ZedBoard, and AD-FMCOMMS3-EBZ. By employing convolutional neural networks and subspace-based methods such as Common Vector Analysis, the project aims to develop a robust recognition framework capable of accurately classifying harmonically modulated signals under phase noise and hardware-induced impairments.