Advancing UAV Communications: A Comprehensive Survey of Cutting-Edge Machine Learning Techniques
C Sun, G Fontanesi, B Canberk… - IEEE Open Journal …, 2024 - ieeexplore.ieee.org
This paper provides a comprehensive overview of the evolution of Machine Learning (ML),
from traditional to advanced, in its application and integration into unmanned aerial vehicle …
from traditional to advanced, in its application and integration into unmanned aerial vehicle …
A transfer learning approach for UAV path design with connectivity outage constraint
The connectivity-aware path design is crucial in the effective deployment of autonomous
unmanned aerial vehicles (UAVs). Recently, reinforcement learning (RL) algorithms have …
unmanned aerial vehicles (UAVs). Recently, reinforcement learning (RL) algorithms have …
Continuous Transfer Learning for UAV Communication-aware Trajectory Design
C Sun, G Fontanesi, SB Chetty, X Liang… - arXiv preprint arXiv …, 2024 - arxiv.org
Deep Reinforcement Learning (DRL) emerges as a prime solution for Unmanned Aerial
Vehicle (UAV) trajectory planning, offering proficiency in navigating high-dimensional …
Vehicle (UAV) trajectory planning, offering proficiency in navigating high-dimensional …
Rate Forecaster based Energy Aware Band Assignment in Multiband Networks
The high frequency communication bands (mm Wave and sub-THz) promise tremendous
data rates, however, they also have very high power consumption which is particularly …
data rates, however, they also have very high power consumption which is particularly …
Wireless Communication with Unmanned Aerial Vehicles: Design Tradeoffs and Machine Learning Techniques
G Fontanesi - 2022 - researchrepository.ucd.ie
Abstract Unmanned Aerial Vehicles (UAVs) are expanding rapidly in a wide range of
wireless network applications. UAVs have inherent mobility, agility, ability to form Line of …
wireless network applications. UAVs have inherent mobility, agility, ability to form Line of …