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Found 5 papers, 0 papers with code
Mobility for Cellular-Connected UAVs: challenges for the network provider
Unmanned Aerial Vehicle (UAV) technology is becoming more prevalent and more diverse in its application.
Networking and Internet Architecture
Energy Aware Deep Reinforcement Learning Scheduling for Sensors Correlated in Time and Space
The proposed mechanism is capable of determining the frequency with which sensors should transmit their updates, to ensure accurate collection of observations, while simultaneously considering the energy available.
Adaptive Height Optimisation for Cellular-Connected UAVs using Reinforcement Learning
On the other hand, BS density can negatively impact UAV QoS, with higher numbers of BSs generating more interference and deteriorating UAV performance.
Radio Access Technology Characterisation Through Object Detection
In contrast to other \ac{ML} methods that can only provide the class of the monitored \acp{RAT}, the solution we propose can recognise not only different \acp{RAT} in shared spectrum, but also identify critical parameters such as inter-frame duration, frame duration, centre frequency, and signal bandwidth by using object detection and a feature extraction module to extract features from spectrograms.
Spectrum Monitoring for Radar Bands using Deep Convolutional Neural Networks
The core of our framework is a deep convolutional neural network (CNN) model that enables Measurement Capable Devices to identify the presence of radar signals in the radio spectrum, even when these signals are overlapped with other sources of interference, such as commercial LTE and WLAN.
