AI for UAV-assisted IoT applications: A comprehensive review

N Cheng, S Wu, X Wang, Z Yin, C Li… - IEEE Internet of …, 2023 - ieeexplore.ieee.org
With the rapid development of the Internet of Things (IoT), there are a dramatically
increasing number of devices, leading to the fact that only using terrestrial infrastructure can …

UAV ad hoc network routing algorithms in space–air–ground integrated networks: Challenges and directions

Y Lu, W Wen, KK Igorevich, P Ren, H Zhang, Y Duan… - Drones, 2023 - mdpi.com
With the rapid development of 5G and 6G communications in recent years, there has been
significant interest in space–air–ground integrated networks (SAGINs), which aim to achieve …

Joint resource allocation and trajectory optimization in UAV-enabled wirelessly powered MEC for large area

Y Zeng, S Chen, Y Cui, J Yang… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
This article investigates a wirelessly powered mobile edge computing (MEC) framework with
the cooperation between an unmanned aerial vehicle (UAV) and a center Cloud. In this …

A survey on applications of unmanned aerial vehicles using machine learning

K Teixeira, G Miguel, HS Silva, F Madeiro - IEEE Access, 2023 - ieeexplore.ieee.org
Unmanned Aerial Vehicles (UAVs) play an important role in many applications, including
health, transport, telecommunications and safe and rescue operations. Their adoption can …

[HTML][HTML] Graph neural networks for intelligent modelling in network management and orchestration: a survey on communications

P Tam, I Song, S Kang, S Ros, S Kim - Electronics, 2022 - mdpi.com
The advancing applications based on machine learning and deep learning in
communication networks have been exponentially increasing in the system architectures of …

Knowledge-driven resource allocation for wireless networks: A WMMSE unrolled graph neural network approach

H Yang, N Cheng, R Sun, W Quan… - IEEE Internet of …, 2024 - ieeexplore.ieee.org
This article proposes a novel knowledge-driven approach for resource allocation in wireless
networks using the graph neural network (GNN) architecture. To meet the millisecond-level …

Energy-efficiency optimization for multiple access in NOMA-enabled space–air–ground networks

S Wang, Z Fei, J Guo, Q Cui, S Durrani… - IEEE Internet of …, 2023 - ieeexplore.ieee.org
Due to the flexible deployment of unmanned aerial vehicles (UAVs) and the wide-area
coverage of satellites, the space–air–ground (SAG) communication network can provide …

A collaborative path planning method for heterogeneous autonomous marine vehicles

J Zhang, Z Wang, G Han, Y Qian… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
Intelligent control of autonomous marine vehicles (AMVs) is one of the essential
technologies for exploring marine resources. In the deep sea with a complicated exploration …

A survey of graph-based resource management in wireless networks-part ii: Learning approaches

Y Dai, L Lyu, N Cheng, M Sheng, J Liu… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
This two-part survey provides a comprehensive review of graph optimization and learning
for resource management in wireless networks. In Part I, we introduced the fundamentals of …

Drone Technology in the Context of the Internet of Things

IA Shah, NZ Jhanjhi, RMA Ujjan - Cybersecurity Issues and …, 2024 - igi-global.com
Drones with integrated internet of things (IoT) technology now have a more comprehensive
range of potential uses, including those for surveillance, agriculture, search and rescue, and …