UAV positioning for throughput maximization using deep learning approaches

YY Munaye, HP Lin, AB Adege, GB Tarekegn - Sensors, 2019 - mdpi.com
The use of unmanned aerial vehicles (UAVs) as a communication platform has great
practical importance for future wireless networks, especially for on-demand deployment for …

UAVs and mobile sensors trajectories optimization with deep learning trained by genetic algorithm towards data collection scenario

Y Pan, Y Yang, H Liu, W Li - Mobile Networks and Applications, 2023 - Springer
In challenging environments like deserts and forests, without communication facilities, data
transmission is a key challenge. To solve this problem, data collection using Unmanned …

UAV positioning for throughput maximization

SU Rahman, YZ Cho - EURASIP Journal on Wireless Communications …, 2018 - Springer
The throughput of a communication system depends on the offered traffic load and the
available capacity to support that load. When an unmanned aerial verhicle (UAV) is …

Machine learning for predictive on-demand deployment of UAVs for wireless communications

Q Zhang, M Mozaffari, W Saad… - 2018 IEEE Global …, 2018 - ieeexplore.ieee.org
In this paper, a novel machine learning (ML) framework is proposed for enabling a
predictive, efficient deployment of unmanned aerial vehicles (UAVs), acting as aerial base …

Learning to Deployment: Data-Driven On-Demand UAV Placement for Throughput Maximization

L Wang, H Zhang, S Guo, D Li… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Unmanned Aerial Vehicles (UAVs) communications appear to be one of the most promising
paradigms for future wireless communication networks, because of their high flexibility in …

A deep learning approach for location independent throughput prediction

J Schmid, M Schneider, A HöB… - 2019 IEEE International …, 2019 - ieeexplore.ieee.org
Mobile communication has become a part of everyday life and is considered to support
reliability and safety in traffic use cases such as conditionally automated driving …

Trajectory prediction of UAV in smart city using recurrent neural networks

K Xiao, J Zhao, Y He, S Yu - ICC 2019-2019 IEEE International …, 2019 - ieeexplore.ieee.org
The 5th generation (5G) wireless network with Unmanned aerial vehicle (UAV) is
considered to be one of the most effective solutions for improving the communication …

A deep neural network approach with attention mechanism to improve the quality of target observation for UAVs

B Liu, X Ning, S Ma, Z Wang - Computers & Industrial Engineering, 2024 - Elsevier
Owing to the limitations of onboard equipment, the direct acquisition of high-resolution
images in unmanned aerial vehicle (UAV) target observation tasks is a challenge. However …

[HTML][HTML] Resource management in 5G networks assisted by UAV base stations: Machine learning for overloaded Macrocell prediction based on users' temporal and …

RD Alfaia, AVF Souto, EHS Cardoso, JPL Araújo… - Drones, 2022 - mdpi.com
The rapid growth of data traffic due to the demands of new services and applications poses
new challenges to the wireless network. Unmanned aerial vehicles (UAVs) can be a solution …

Deep learning architecture for UAV traffic-density prediction

A Alharbi, I Petrunin, D Panagiotakopoulos - Drones, 2023 - mdpi.com
The research community has paid great attention to the prediction of air traffic flows.
Nonetheless, research examining the prediction of air traffic patterns for unmanned aircraft …