March 13, 2026
In the paper “Artificial Intelligence for Wireless Communications: The InSecTT Perspective,” VeNIT Lab examines AI for wireless networks!
Wireless networks are becoming too complex to manage with traditional optimisation methods alone. VeNIT Lab (Marmara University) Director Prof. Dr. Mujdat Soyturk and VeNIT Lab Researcher Yavuz Selim Bostancı, together with other researchers, contributed to the paper “Artificial Intelligence for Wireless Communications: The InSecTT Perspective”.
The study examines how AI techniques can improve wireless network performance in areas such as interference mitigation, beamforming optimisation and channel prediction. Beamfo
rming optimisation refers to adjusting the direction and strength of wireless signals to improve connectivity, while channel prediction uses machine learning to anticipate changes in signal quality.
Developed within the InSecTT research framework, the work explores reusable AI building blocks designed for wireless communication systems. These components aim to support applications where reliable and adaptive connectivity is essential.
For example, in automotive systems, AI can enable real-time vehicle-to-vehicle communication to improve safety, while in industrial IoT environments, machine learning models can optimise sensor data transmission and reduce energy consumption.
The paper highlights how integrating trustworthy AI into wireless infrastructures can support critical systems such as connected mobility platforms and industrial automation.
You can reach the paper through this link: https://ieeexplore.ieee.org/document/11112099