User-centric intelligent UAV swarm networks: performance analysis and design insight
W Huang, J Peng, H Zhang - IEEE access, 2019 - ieeexplore.ieee.org
To enhance the network coverage and capacity, unmanned aerial vehicle (UAV)
communication has become a promising technology thanks to the high mobility and the …
communication has become a promising technology thanks to the high mobility and the …
Joint power allocation and 3D deployment for UAV-BSs: A game theory based deep reinforcement learning approach
Ultra-dense unmanned aerial vehicle (UAV) plays an important role in the field of
communications due to its flexibility and low-cost feature. Ultra-dense unnamed aerial …
communications due to its flexibility and low-cost feature. Ultra-dense unnamed aerial …
Mobility management for cellular-connected UAVs: A learning-based approach
MMU Chowdhury, W Saad… - 2020 IEEE international …, 2020 - ieeexplore.ieee.org
The pervasiveness of the wireless cellular network can be a key enabler for the deployment
of autonomous unmanned aerial vehicles (UAVs) in beyond visual line of sight scenarios …
of autonomous unmanned aerial vehicles (UAVs) in beyond visual line of sight scenarios …
Machine learning-based user scheduling in integrated satellite-haps-ground networks
Integrated space-air-ground networks promise to offer a valuable solution space for
empowering the sixth generation of communication networks (6G), particularly in the context …
empowering the sixth generation of communication networks (6G), particularly in the context …
Cellular UAV-to-device communications: Trajectory design and mode selection by multi-agent deep reinforcement learning
In the current unmanned aircraft systems (UASs) for sensing services, unmanned aerial
vehicles (UAVs) transmit their sensory data to terrestrial mobile devices over the unlicensed …
vehicles (UAVs) transmit their sensory data to terrestrial mobile devices over the unlicensed …
Traffic-aware adaptive deployment for UAV-aided communication networks
Unmanned aerial vehicle (UAV) can be used as an aerial base station to provide rapid
wireless connectivity to ground users. Given UAV's agility and mobility, a key problem is how …
wireless connectivity to ground users. Given UAV's agility and mobility, a key problem is how …
FED-UP: Federated deep reinforcement learning-based UAV path planning against hostile defense system
In military operations, unmanned aerial vehicles (UAVs) have been heavily utilized in recent
years. However, due to the antenna installment regulation, UAVs cannot be controlled by …
years. However, due to the antenna installment regulation, UAVs cannot be controlled by …
UAV-assisted online machine learning over multi-tiered networks: A hierarchical nested personalized federated learning approach
We investigate training machine learning (ML) models across a set of geo-distributed,
resource-constrained clusters of devices through unmanned aerial vehicles (UAV) swarms …
resource-constrained clusters of devices through unmanned aerial vehicles (UAV) swarms …
A Deep Reinforcement Learning Based Approach for Optimizing Trajectory and Frequency in Energy Constrained Multi-UAV Assisted MEC System
B Shi, Z Chen, Z Xu - IEEE Transactions on Network and …, 2024 - ieeexplore.ieee.org
Mobile Edge Computing (MEC) is a technology that shows great promise in enhancing the
computational power of smart devices (SDs) in the Internet of Things (IoT). However, the …
computational power of smart devices (SDs) in the Internet of Things (IoT). However, the …
Deep Reinforcement Learning Based Placement for Integrated Access Backhauling in UAV-Assisted Wireless Networks
The advent of fifth generation 5G networks has opened new avenues for enhancing
connectivity, particularly in challenging environments, such as remote areas or disaster …
connectivity, particularly in challenging environments, such as remote areas or disaster …