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Continuous Transfer Learning for UAV Communication-aware Trajectory Design
Deep Reinforcement Learning (DRL) emerges as a prime solution for Unmanned Aerial Vehicle (UAV) trajectory planning, offering proficiency in navigating high-dimensional spaces, adaptability to dynamic environments, and making sequential decisions based on real-time feedback.
Enhancing Energy Efficiency in O-RAN Through Intelligent xApps Deployment
The proliferation of 5G technology presents an unprecedented challenge in managing the energy consumption of densely deployed network infrastructures, particularly Base Stations (BSs), which account for the majority of power usage in mobile networks.
Multi-Objective Deep Reinforcement Learning for 5G Base Station Placement to Support Localisation for Future Sustainable Traffic
This work assumes a pre-deployed BS and another BS is required to be added to support both localisation accuracy and coverage rate in an urban city scenario.
Deep Reinforcement Learning for Dynamic Band Switch in Cellular-Connected UAV
Results reveal that the smart approach is able in a high threshold regime to reduce the number of radio failures and band switches while reaching the desired destination.
Attosecond Pulse-shaping using a seeded free-electron laser
Here we show the first demonstration of reproducible generation of high energy ($\mathrm{\mu}$J level) attosecond waveforms using a seeded Free Electron Laser.
Optics Atomic Physics
