25 citations · 42 across the 5 of their papers we have counts for
8 papers · 1 filter
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…
Performance Evaluation for the Co-existence of eMBB and URLLC Networks: Synchronized versus Unsynchronized TDD
Ursula Challita, Kimmo Hiltunen, Miurel Tercero
To ensure the high level of automation required in today's industrial applications, next-generation wireless networks must enable real-time control and automation of dynamic proces…
Machine Learning for Wireless Connectivity and Security of Cellular-Connected UAVs
Ursula Challita, Aidin Ferdowsi, Mingzhe Chen +1
Cellular-connected unmanned aerial vehicles (UAVs) will inevitably be integrated into future cellular networks as new aerial mobile users. Providing cellular connectivity to UAVs w…
Cellular-Connected UAVs over 5G: Deep Reinforcement Learning for Interference Management
Ursula Challita, Walid Saad, Christian Bettstetter
In this paper, an interference-aware path planning scheme for a network of cellular-connected unmanned aerial vehicles (UAVs) is proposed. In particular, each UAV aims at achieving…
Deep Learning for Reliable Mobile Edge Analytics in Intelligent Transportation Systems
Aidin Ferdowsi, Ursula Challita, Walid Saad
Intelligent transportation systems (ITSs) will be a major component of tomorrow's smart cities. However, realizing the true potential of ITSs requires ultra-low latency and reliabl…
Artificial Neural Networks-Based Machine Learning for Wireless Networks: A Tutorial
Mingzhe Chen, Ursula Challita, Walid Saad +2
Next-generation wireless networks must support ultra-reliable, low-latency communication and intelligently manage a massive number of Internet of Things (IoT) devices in real-time,…