90 citations · 195 across the 9 of their papers we have counts for
9 papers
Federated Learning with Multi-resolution Model Broadcast
Henrik Rydén, Reza Moosavi, Erik G. Larsson
In federated learning, a server must periodically broadcast a model to the agents. We propose to use multi-resolution coding and modulation (also known as non-uniform modulation) f…
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…
Fueling the Next Quantum Leap in Cellular Networks: Embracing AI in 5G Evolution towards 6G
Xingqin Lin, Mingzhe Chen, Henrik Rydén +6
Cellular networks, such as 5G systems, are becoming increasingly complex for supporting various deployment scenarios and applications. Embracing artificial intelligence (AI) in 5G…
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…
Positioning for the Internet of Things: A 3GPP Perspective
Xingqin Lin, Johan Bergman, Fredrik Gunnarsson +5
Many use cases in the Internet of Things (IoT) will require or benefit from location information, making positioning a vital dimension of the IoT. The 3rd Generation Partnership Pr…