464 citations · 702 across the 12 of their papers we have counts for
13 papers
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…
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…
Noise Learning Based Denoising Autoencoder
Woong-Hee Lee, Mustafa Ozger, Ursula Challita +1
This letter introduces a new denoiser that modifies the structure of denoising autoencoder (DAE), namely noise learning based DAE (nlDAE). The proposed nlDAE learns the noise of th…
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…
Robust Deep Reinforcement Learning for Security and Safety in Autonomous Vehicle Systems
Aidin Ferdowsi, Ursula Challita, Walid Saad +1
To operate effectively in tomorrow's smart cities, autonomous vehicles (AVs) must rely on intra-vehicle sensors such as camera and radar as well as inter-vehicle communication. Suc…
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,…
Network Formation in the Sky: Unmanned Aerial Vehicles for Multi-hop Wireless Backhauling
Ursula Challita, Walid Saad
To reap the benefits of dense small base station (SBS) deployment, innovative backhaul solutions are needed in order to manage scenarios in which high-speed ground backhaul links a…
Proactive Resource Management for LTE in Unlicensed Spectrum: A Deep Learning Perspective
Ursula Challita, Li Dong, Walid Saad
LTE in unlicensed spectrum using licensed assisted access LTE (LTE-LAA) is a promising approach to overcome the wireless spectrum scarcity. However, to reap the benefits of LTE-LAA…
Holistic Small Cell Traffic Balancing across Licensed and Unlicensed Bands
Ursula Challita, Mahesh K. Marina
Due to the dramatic growth in mobile data traffic on one hand and the scarcity of the licensed spectrum on the other hand, mobile operators are considering the use of unlicensed ba…