2 citations · 2 across the 3 of their papers we have counts for
7 papers
Mobility, traffic and radio channel prediction: 5G and beyond applications
Henrik Rydén, Alex Palaios, László Hévizi +3
Machine learning (ML) is an important component for enabling automation in Radio Access Networks (RANs). The work on applying ML for RAN has been under development for many years a…
When Machine Learning Meets Wireless Cellular Networks: Deployment, Challenges, and Applications
Ursula Challita, Henrik A. Ryden, Hugo Tullberg
Artificial intelligence (AI) powered wireless networks promise to revolutionize the conventional operation and structure of current networks from network design to infrastructure m…
5G Handover using Reinforcement Learning
Vijaya Yajnanarayana, Henrik Rydén, László Hévizi
In typical wireless cellular systems, the handover mechanism involves reassigning an ongoing session handled by one cell into another. In order to support increased capacity requir…
5G New Radio Evolution Meets Satellite Communications: Opportunities, Challenges, and Solutions
Xingqin Lin, Björn Hofström, Eric Wang +10
The 3rd generation partnership project (3GPP) completed the first global 5th generation (5G) new radio (NR) standard in its Release 15, paving the way for making 5G a commercial re…
Rogue Drone Detection: A Machine Learning Approach
Henrik Rydén, Sakib Bin Redhwan, Xingqin Lin
The emerging, practical and observed issue of how to detect rogue drones that carry terrestrial user equipment (UEs) on mobile networks is addressed in this paper. This issue has d…
A Telecom Perspective on the Internet of Drones: From LTE-Advanced to 5G
Guang Yang, Xingqin Lin, Yan Li +5
Drones are driving numerous and evolving use cases, and creating transformative socio-economic benefits. Drone operation needs wireless connectivity for communication between drone…