Deemah Tashman, a member of Lincs lab, has her journal paper accepted and published in IEEE Communications Surveys & Tutorials. The paper titled “Advances in Machine Learning-Driven Cognitive Radio for Wireless Networks: A Survey” is a result of collaboration with Nada Abdel Khalek, Ph.D. candidate at Concordia University and Prof. Walaa Hamouda, Ph.D., P.Eng., Tier I Canada Research Chair at Concordia University.

This paper is a survey that provides an in-depth analysis of the integration of Machine Learning-based Cognitive Radio in a wide range of emerging wireless networks, including the Internet of Things, mobile communications (vehicular and railway), and unmanned aerial vehicle communications. By combining ML-based CR and emerging wireless networks, Intelligent, efficient, and ubiquitous wireless communication systems that satisfy spectrum-hungry applications and services of next-generation networks can be created . The key motivation for using intelligent CR in each type of wireless network is highlighted, and a full review of the existing state-of-the-art ML approaches that address pressing challenges, including energy efficiency, interference, throughput, latency, and security, is presented.

IEEE Communications Surveys & Tutorials is a prestigious journal published by the IEEE Communications Society with an Impact Factor of 35.6. This journal is known for its comprehensive surveys, tutorials, and peer-reviewed articles covering all aspects of communication systems and networks.

For more detail about the paper, visit Advances in Machine Learning-Driven Cognitive Radio for Wireless Networks: A Survey