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AI-based Radio Resource Management and Trajectory Design for PD-NOMA Communication in IRS-UAV Assisted Networks
[article]
2021
arXiv
pre-print
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We investigate the benefits of the UAV-IRS on the internet of things (IoT) networks that improve the freshness of collected data of the IoT devices via optimizing power, sub-carrier, and trajectory variables ...
, and utilize the power-domain non-orthogonal multiple access (PD-NOMA) scheme in the uplink. ...
in [22] investigate the UAV-assisted wireless powered IoT system and study a joint energy transfer and data collection time allocation and a UAV's trajectory planning problem. ...
arXiv:2111.03869v1
fatcat:mh5qckhim5hb7oxcjypjlqasfy
Deep Reinforcement Learning Based Freshness-Aware Path Planning for UAV-Assisted Edge Computing Networks with Device Mobility
2022
Remote Sensing
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Then, the path planning problem is formulated to simultaneously minimize the AoIs of mobile devices and the energy consumption of the UAV, where the movement randomness of IoT devices are taken into account ...
As unmanned aerial vehicles (UAVs) can provide flexible and efficient services concerning the sparse network distribution, we study a UAV-assisted mobile edge computing (MEC) network. ...
The achieved AoI of IoT devices is studied in [15] [16] [17] [18] by optimizing the UAV trajectory. In [17] , the achieved AoI is minimized for UAV-assisted wireless powered IoT network. ...
doi:10.3390/rs14164016
fatcat:mhwmk54uengs5k7rchotai5zne
Deep Reinforcement Learning for Fresh Data Collection in UAV-assisted IoT Networks
[article]
2020
arXiv
pre-print
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In this paper, we investigate the fresh data collection problem in UAV-assisted IoT networks. ...
We formulate a Markov Decision Process (MDP) to find the optimal flight trajectory of the UAV and transmission scheduling of the sensors that minimizes the weighted sum of the age of information (AoI). ...
In this paper, we investigate the fresh data collection problem in UAV-assisted IoT networks. ...
arXiv:2003.00391v1
fatcat:tzajmwjphnbvlkwc2sdienz5zi
UAV Trajectory Planning for AoI-Minimal Data Collection in UAV-Aided IoT Networks by Transformer
2022
IEEE Transactions on Wireless Communications
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2023 pre-print arXiv:2401.02425v1 fatcat:6wf3xr7735bbloyzohrfhx5zka
An optimization problem is formulated to minimize the total AoI of the collected data by the UAV from the ground IoT network. ...
Maintaining freshness of data collection in Internet-of-Things (IoT) networks has attracted increasing attention. ...
Due to the importance of AoI, a number of studies have been carried out on AoI-oriented data collection in UAV-assisted wireless networks. ...
doi:10.1109/twc.2022.3204438
fatcat:ghbzgeoo2vcgrd72rbxxk7snem
Deep Reinforcement Learning for Joint Cruise Control and Intelligent Data Acquisition in UAVs-Assisted Sensor Networks
[article]
2023
arXiv
pre-print
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Unmanned aerial vehicle (UAV)-assisted sensor networks (UASNets), which play a crucial role in creating new opportunities, are experiencing significant growth in civil applications worldwide. ...
Our proposal to address this challenge is to minimize packet loss by jointly optimizing the velocity controls and data collection schedules of multiple UAVs.Furthermore, in UASNets, swift movements of ...
In Zhou et al. (2019) , trajec-tory planning of the UAV is performed to reduce the AoI in a UAV-assisted IoT network. ...
arXiv:2312.09953v1
fatcat:y2few4zwzzgmlcv3c3ajslfbsq
Bayesian Optimization Enhanced Deep Reinforcement Learning for Trajectory Planning and Network Formation in Multi-UAV Networks
[article]
2022
arXiv
pre-print
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The trajectory planning aims to collect all GUs' data, while the UAVs' network formation optimizes the multi-hop UAV network topology to minimize the energy consumption and transmission delay. ...
The simulation results reveal close spatial-temporal couplings between the UAVs' trajectory planning and network formation. ...
The authors in [29] studied the AoI minimization in a UAV-assisted wireless network with RF power transfer. ...
arXiv:2212.13396v1
fatcat:6clodkc4mffyplxzyad5aut5im
The UAV Trajectory Optimization for Data Collection from Time-Constrained IoT Devices: A Hierarchical Deep Q-Network Approach
2022
Applied Sciences
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Moreover, we hope that UAVs can perform long-term data collection tasks in dynamic scenarios within a constantly changing age of information (AoI) and within their own power levels. ...
However, previous studies on the UAV-assisted data acquisition systems focused mainly on shortening the acquisition time, reducing the energy consumption, and increasing the amount of collected data, but ...
In [15, 22] , the authors formulated the fresh data collection problem in UAV-assisted IoT networks as a Markov decision process (MDP) and used a DRL-based approach to minimize the AoI. Zhou et al. ...
doi:10.3390/app12052546
fatcat:jdt7askxergfdiph7xw2bsplk4
Two-Hop Age of Information Scheduling for Multi-UAV Assisted Mobile Edge Computing: FRL vs MADDPG
[article]
2022
arXiv
pre-print
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In our network we have two types of agents with different states and actions but with the same policy. Our FRL enables us to handle the two-step AoI minimization and UAV trajectory problems. ...
To maintain the freshness of the tasks, we formulate the AoI minimization in two-hop communication framework, the first hop at the UAVs and the second hop at the BS. ...
In [21] , the authors investigate age-optimal trajectory planning in wireless sensor networks using UAVs to collect data from the ground sensor. ...
arXiv:2206.09488v1
fatcat:ni3nkm4nerbmpomqc3y62y7jwi
Guest Editorial Special Issue on UAV Communications in 5G and Beyond Networks—Part II
2021
IEEE Journal on Selected Areas in Communications
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The article "A UAV-assisted ubiquitous trust communication system in 5G and beyond networks" constructs a UAV-assisted ubiquitous trusted communication system to provide trusted data collection and communication ...
The article "UAV-enabled covert wireless data collection" studies the problem of single UAV wireless data collection under covertness constraints from ground users. ...
doi:10.1109/jsac.2021.3090897
fatcat:22i7u6tzevb6vgdrwflhzsv34u
Machine Learning-Aided Operations and Communications of Unmanned Aerial Vehicles: A Contemporary Survey
[article]
2022
arXiv
pre-print
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and mission planning, and aerodynamic control and operation. ...
It is also unveiled that the reliability and trust of ML in UAV operations and applications require significant attention before full automation of UAVs and potential cooperation between UAVs and humans ...
[209] studied a twin delayed DDPG (TD3) model to minimize the AoI and energy consumption of the UAV-assisted IoT network. ...
arXiv:2211.04324v1
fatcat:2ytdjhxm5zfkpjjc4ajxb5lc6q
AoI-minimizing Scheduling in UAV-relayed IoT Networks
[article]
2021
arXiv
pre-print
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To address this, we propose scheduling policies for Age of Information (AoI) minimization in such two-hop UAV-relayed IoT networks. ...
In order to ensure timely delivery of information to the TBS (from all IoT devices), optimal scheduling of time-sensitive information over two hop UAV-relayed IoT networks (i.e., IoT device to the UAV ...
There has been active research on designing scheduling policies to minimize AoI in UAV-assisted IoT networks [8] , general IoT networks [9] , vehicular networks, and other timesensitive control applications ...
arXiv:2107.05181v5
fatcat:trkpjswvtveznkeypww2eiqq4u
Blockchain-Envisioned Unmanned Aerial Vehicle Communications in Space-Air-Ground Integrated Network: A Review
2021
Intelligent and Converged Networks
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In this work, we review the role of UAVs in the SAGIN. Then, three applications of the blockchain-envisioned UAV network are introduced through several classifications. ...
The traditional UAV network architecture is not adequate to meet the challenges presented by the SAGIN, and an effective and secure space-air-ground integrated UAV network needs to be constructed. ...
Acknowledgment This work was supported by the National Natural Science Foundation of China (Nos. 61563004 and 61761007). ...
doi:10.23919/icn.2021.0018
fatcat:sdeg6bbicjbildtlzvtb6hn4wa
Trajectory Design for UAV-Based Internet-of-Things Data Collection: A Deep Reinforcement Learning Approach
[article]
2021
arXiv
pre-print
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In this paper, we investigate an unmanned aerial vehicle (UAV)-assisted Internet-of-Things (IoT) system in a sophisticated three-dimensional (3D) environment, where the UAV's trajectory is optimized to ...
efficiently collect data from multiple IoT ground nodes. ...
Fig. 1 . 1 UAV-assisted IoT data collection system.
Fig. 2 . 2 TD3-based trajectory design for UAV-assisted IoT data collection system. ...
arXiv:2107.11015v1
fatcat:djr4jox45jhe7khu7jmv5eadbm
Age Minimization in Massive IoT via UAV Swarm: A Multi-agent Reinforcement Learning Approach
[article]
2023
arXiv
pre-print
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The target is to minimize the overall age of information in the IoT network. ...
A robust solution is to deploy a large number of UAVs (UAV swarm) to provide coverage and a better line of sight (LoS) for the IoT network. ...
ACKNOWLEDGMENTS This work is partially supported by Academy of Finland, 6G Flagship program (Grant no. 346208) and FIREMAN (Grant no. 326301), and the European Commission through the Horizon Europe project ...
arXiv:2309.14757v1
fatcat:qlkcwifjnjbqdbrho25nh5h7tq
Multi-objective Optimization for Data Collection in UAV-assisted Agricultural IoT
[article]
2024
arXiv
pre-print
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To improve the network coverage and performance of wireless communication, unmanned aerial vehicles (UAVs) have been introduced in diverse wireless networks, therefore in this work we consider employing ...
To this end, we first formulate a UAV-assisted data collection multi-objective optimization problem (UDCMOP) to efficiently collect the data from agricultural sensing devices. ...
[20] investigate the problem of fresh data collection in UAV-assisted IoT networks to minimize the weighted sum of AoI. ...
arXiv:2403.12985v1
fatcat:ngaqe6bh7rd6fa7n2zhz7ixlaa
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