A novel energy-efficiency framework for UAV-assisted networks using adaptive deep reinforcement learning

K Seerangan, M Nandagopal, T Govindaraju… - Scientific Reports, 2024 - nature.com
In the air-to-ground transmissions, the lifespan of the network is based on the “unmanned
aerial vehicle's (UAV)” life span because of the limited battery capacity. Thus, the …

[HTML][HTML] A distributed task allocation method for multi-UAV systems in communication-constrained environments

S Yan, J Feng, F Pan - Drones, 2024 - mdpi.com
This paper addresses task allocation to multi-UAV systems in time-and communication-
constrained environments by presenting an extension to the novel heuristic performance …

Joint UAV 3D Trajectory Design and Resource Scheduling for Space-Air-Ground Integrated Power IoRT: A Deep Reinforcement Learning Approach

J Liu, X Zhao, P Qin, F Du, Z Chen… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The terrain-independent space-air-ground integrated power Internet of Remote Things (SAG-
PIoRT) is able to bring efficient communication services with seamless coverage for sensors …

RIS-Assisted Robust Beamforming for UAV Anti-Jamming and Eavesdropping Communications: A Deep Reinforcement Learning Approach

C Zou, C Li, Y Li, X Yan - Electronics, 2023 - mdpi.com
The reconfigurable intelligent surface (RIS) has been widely recognized as a rising
paradigm for physical layer security due to its potential to substantially adjust the …

Energy efficient deployment of aerial base stations for mobile users in multi-hop UAV networks

K Ryu, W Kim - Ad Hoc Networks, 2024 - Elsevier
Unmanned aerial vehicles (UAVs) are popularly considered as aerial base stations in a Low-
Altitude Platform (LAP) to provide wireless connections to ground users in disaster and …

Short vs. Long-term Coordination of Drones: When Distributed Optimization Meets Deep Reinforcement Learning

C Qin, E Pournaras - arXiv preprint arXiv:2311.09852, 2023 - arxiv.org
Swarms of smart drones, with the support of charging technology, can provide completing
sensing capabilities in Smart Cities, such as traffic monitoring and disaster response …

Deep Reinforcement Learning based running-track path design for fixed-wing UAV assisted mobile relaying network

T Wang, X Ji, X Zhu, C He, JF Gu - Vehicular Communications, 2024 - Elsevier
This paper studies a fixed-wing unmanned aerial vehicle (UAV) assisted mobile relaying
network (FUAVMRN), where a fixed-wing UAV employs an out-band full-duplex relaying …

Throughput Maximization in Delay-Critical and Energy-Aware SW-UAV-WNs Using Q-Learning

SR Yeduri, N Sharma, OJ Pandey… - IEEE Open Journal …, 2024 - ieeexplore.ieee.org
Unmanned aerial vehicles (UAVs) are getting significant attention from both researchers and
the industry due to their wide range of applications. Remote sensing is one such application …