Self-learning Bayesian generative models for jammer detection in cognitive-UAV-radios
Unmanned Aerial Vehicles (UAVs) attracted both industry and research community owing to
their fascinating features like mobility, deployment flexibility and strong Line of Sight (LoS) …
their fascinating features like mobility, deployment flexibility and strong Line of Sight (LoS) …
Reconfigurable intelligent surface-assisted multi-UAV networks: Efficient resource allocation with deep reinforcement learning
KK Nguyen, SR Khosravirad… - IEEE Journal of …, 2021 - ieeexplore.ieee.org
In this paper, we propose reconfigurable intelligent surface (RIS)-assisted unmanned aerial
vehicles (UAVs) networks that can utilise both advantages of UAV's agility and RIS's …
vehicles (UAVs) networks that can utilise both advantages of UAV's agility and RIS's …
A novel federated learning-based smart power and 3D trajectory control for fairness optimization in secure UAV-assisted MEC services
R Karmakar, G Kaddoum… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Unmanned aerial vehicles (UAVs)-aided mobile-edge computing (MEC) systems face
several challenges that hinder their practical implementation. First, the broadcast nature of …
several challenges that hinder their practical implementation. First, the broadcast nature of …
Learning-based robust and secure transmission for reconfigurable intelligent surface aided millimeter wave UAV communications
In this letter, we study the robust and secure transmission in the millimeter-wave (mmWave)
unmanned aerial vehicle (UAV) communication assisted by a reconfigurable intelligent …
unmanned aerial vehicle (UAV) communication assisted by a reconfigurable intelligent …
Multiple residual dense networks for reconfigurable intelligent surfaces cascaded channel estimation
Reconfigurable intelligent surface (RIS) constitutes an essential and promising paradigm
that relies programmable wireless environment and provides capability for space-intensive …
that relies programmable wireless environment and provides capability for space-intensive …
Machine learning empowered trajectory and passive beamforming design in UAV-RIS wireless networks
A novel framework is proposed for integrating reconfigurable intelligent surfaces (RIS) in
unmanned aerial vehicle (UAV) enabled wireless networks, where an RIS is deployed for …
unmanned aerial vehicle (UAV) enabled wireless networks, where an RIS is deployed for …
Cognition in UAV-aided 5G and beyond communications: A survey
In recent years, unmanned aerial vehicles (UAVs) have attained significant interest in
different applications including aerial surveillance, providing wireless coverage, precision …
different applications including aerial surveillance, providing wireless coverage, precision …
UAV-enabled covert federated learning
Integrating unmanned aerial vehicles (UAVs) with federated learning (FL) has been seen as
a promising paradigm for dealing with the massive amounts of data generated by intelligent …
a promising paradigm for dealing with the massive amounts of data generated by intelligent …
Cooperative multi-agent deep reinforcement learning for reliable and energy-efficient mobile access via multi-UAV control
This paper addresses a novel multi-agent deep reinforcement learning (MADRL)-based
positioning algorithm for multiple unmanned aerial vehicles (UAVs) collaboration (ie, UAVs …
positioning algorithm for multiple unmanned aerial vehicles (UAVs) collaboration (ie, UAVs …
Multi-UAV navigation for partially observable communication coverage by graph reinforcement learning
In this paper, we aim to design a deep reinforcement learning (DRL) based control solution
to navigating a swarm of unmanned aerial vehicles (UAVs) to fly around an unexplored …
to navigating a swarm of unmanned aerial vehicles (UAVs) to fly around an unexplored …