College of Electronics Engineering, University of Nineveh discussed a master dissertation on machine learning-assisted signal processing for communication systems by the postgraduate student, Ms. Manar Talal Muhammad Ali.
The dissertation aimed at applying self-interference cancellation (SIC) techniques based on machine learning to effectively mitigate the signal interference (SI) imposed by IBFD communications.
The dissertation proposed In-Band Full Duplex (IBFD) communication as a solution to multiply the capacity to manage spectral efficiency and improve throughput, especially in bandwidth-limited environments.
The dissertation concluded that machine learning-based SIC techniques demonstrated significant improvements in cancellation rates and spectral efficiency, leading to enhance overall system performance compared to conventional techniques.
