The project, prepared by Dr. Mehmet Hakan Durak, a faculty member of the Department of Electrical-Electronics Engineering at Erzurum Technical University (ETU) Faculty of Engineering and Architecture, and Dr. Murat Can Karakoc, a faculty member of the Department of Electrical-Electronics Engineering at Ankara Yildirim Beyazit University (AYBU) Faculty of Engineering and Natural Sciences, has been awarded support under the TUBITAK 1002-A Rapid Support Program.

The project, titled "Sub-Space and Machine Learning Based Automatic Modulation Recognition in Harmonically Modulated Signals," aims to investigate the effects of nonlinear phase transformations and spectral distortions caused by the harmonic modulation process on automatic modulation recognition systems.

This project, focused on next-generation communication and signal intelligence technologies, will be conducted under the leadership of Dr. Murat Can Karakoc, a faculty member at AYBU. Dr. Karakoc, a faculty member at ETU, is also involved in the project. Associate Professor Mehmet Hakan Durak will serve as a researcher. The project will also provide scholarship support to a graduate student studying at ETU (Eskisehir Technical University).

The methods to be developed in the project will be tested in conditions where phase noise, frequency shift, nonlinearity, and spectral distortions originating from real communication equipment are present, as well as in ideal datasets created in a laboratory environment.

Within the scope of the study, experimental signals will be generated and measurements will be performed in a real radio frequency environment using ADALM-Pluto SDR, ZedBoard, and AD-FMCOMMS3-EBZ platforms. By analyzing the obtained data using sub-space methods and machine learning techniques, the aim is to develop a robust classification structure that can reliably operate, especially under conditions with high phase noise and hardware-related distortions.

"To Be Tested in Real Communication Environments"

Commenting on the project, Associate Professor Mehmet Hakan Durak stated that they will investigate the effects of nonlinear phase shifts and spectral distortions resulting from harmonic modulation on the performance of automatic modulation recognition systems.

Durak stated that the data obtained from experiments to be conducted in a real radio frequency environment will be analyzed using sub-space methods and machine learning techniques, and that they aim to develop a new classification structure that can reliably operate under conditions with high phase noise and hardware-related distortions.

Durak noted that they expect the outputs obtained within the scope of the project to contribute to studies in the fields of software-defined radio systems, intelligent communication applications, spectrum monitoring, and signal intelligence.

Corporate Communications and Promotion Directorate, August 7, 2026