activity
20172021
most citedDeep Learning for Reliable Mobile Edge Analytics in Intelligent Transportation Systems

25 citations · 36 across the 4 of their papers we have counts for

collaborators

7 papers

cs.NI2021

Deep Reinforcement Learning for Dynamic Spectrum Sharing of LTE and NR

Ursula Challita, David Sandberg

In this paper, a proactive dynamic spectrum sharing scheme between 4G and 5G systems is proposed. In particular, a controller decides on the resource split between NR and LTE every…

eess.SP2021

QoE Optimization for Live Video Streaming in UAV-to-UAV Communications via Deep Reinforcement Learning

Liyana Adilla binti Burhanuddin, Xiaonan Liu, Yansha Deng +2

A challenge for rescue teams when fighting against wildfire in remote areas is the lack of information, such as the size and images of fire areas. As such, live streaming from Unma…

cs.IT2019

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…

cs.IT2019

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…

cs.IT2018

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…

cs.IT201725 cited

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…