Adaptive coding and modulation-aided mobile relaying for millimeter-wave flying ad hoc networks
Adaptive coding and modulation-aided mobile relaying for millimeter-wave flying ad hoc networks
The emerging drone swarms are capable of carrying out sophisticated tasks in support of demanding Internet of Things (IoT) applications by synergistically working together. However, the target area may be out of the coverage of the ground station (GS) and it may be impractical to deploy a large number of drones in the target area due to cost, electromagnetic interference, and flight-safety regulations. By exploiting the innate agility and mobility of unmanned aerial vehicles (UAVs), we conceive a mobile relaying-assisted drone swarm network architecture, which is capable of extending the coverage of the GS and enhancing the effective end-to-end throughput. Explicitly, a swarm of drones forms a data-collecting drone swarm (DCDS) designed for sensing and collecting data with the aid of their mounted cameras and/or sensors, and a powerful relay-UAV (RUAV) acts as a mobile relay for conveying data between the DCDS and a GS. Given a time period, in order to maximize the data delivered while minimizing the delay imposed, we harness an $\epsilon $ -multiple-objective genetic algorithm ( $\epsilon $ -MOGA)-assisted Pareto-optimization scheme. Our simulation results demonstrate that the proposed mobile relaying is capable of delivering more data. As specific examples investigated in our simulations, our mobile relaying-assisted drone swarm network is capable of delivering 45.38% more data than the benchmark solutions, when a stationary relay is available, and it is capable of delivering 26.86% more data than the benchmark solutions when no stationary relay is available.
Autonomous aerial vehicles, Drones, Millimeter wave communication, Optimization, Relays, Routing, Throughput, Unmanned aerial vehicle, adaptive coding and modulation, aeronautical communications, beamforming, drone swarm, millimeter wave, unmanned aerial vehicle (UAV), Adaptive coding and modulation (ACM), millimeter wave (mmWave)
3282-3301
Zhang, Jiankang
c6c025b3-6576-4f9d-be95-57908e61fa88
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Chai, Wei Koong
e277a6a9-e916-48ec-a8c8-e62f3b6d30c0
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
15 January 2024
Zhang, Jiankang
c6c025b3-6576-4f9d-be95-57908e61fa88
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Chai, Wei Koong
e277a6a9-e916-48ec-a8c8-e62f3b6d30c0
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Zhang, Jiankang, Chen, Sheng, Chai, Wei Koong and Hanzo, Lajos
(2024)
Adaptive coding and modulation-aided mobile relaying for millimeter-wave flying ad hoc networks.
IEEE Internet of Things Journal, 11 (2), .
(doi:10.1109/JIOT.2023.3296058).
Abstract
The emerging drone swarms are capable of carrying out sophisticated tasks in support of demanding Internet of Things (IoT) applications by synergistically working together. However, the target area may be out of the coverage of the ground station (GS) and it may be impractical to deploy a large number of drones in the target area due to cost, electromagnetic interference, and flight-safety regulations. By exploiting the innate agility and mobility of unmanned aerial vehicles (UAVs), we conceive a mobile relaying-assisted drone swarm network architecture, which is capable of extending the coverage of the GS and enhancing the effective end-to-end throughput. Explicitly, a swarm of drones forms a data-collecting drone swarm (DCDS) designed for sensing and collecting data with the aid of their mounted cameras and/or sensors, and a powerful relay-UAV (RUAV) acts as a mobile relay for conveying data between the DCDS and a GS. Given a time period, in order to maximize the data delivered while minimizing the delay imposed, we harness an $\epsilon $ -multiple-objective genetic algorithm ( $\epsilon $ -MOGA)-assisted Pareto-optimization scheme. Our simulation results demonstrate that the proposed mobile relaying is capable of delivering more data. As specific examples investigated in our simulations, our mobile relaying-assisted drone swarm network is capable of delivering 45.38% more data than the benchmark solutions, when a stationary relay is available, and it is capable of delivering 26.86% more data than the benchmark solutions when no stationary relay is available.
Text
IOT-2023-accepted
- Accepted Manuscript
Text
IEEEIoT2024-Jan
- Version of Record
Restricted to Repository staff only
Request a copy
More information
Accepted/In Press date: 13 July 2023
e-pub ahead of print date: 17 July 2023
Published date: 15 January 2024
Additional Information:
Publisher Copyright:
© 2014 IEEE.
Keywords:
Autonomous aerial vehicles, Drones, Millimeter wave communication, Optimization, Relays, Routing, Throughput, Unmanned aerial vehicle, adaptive coding and modulation, aeronautical communications, beamforming, drone swarm, millimeter wave, unmanned aerial vehicle (UAV), Adaptive coding and modulation (ACM), millimeter wave (mmWave)
Identifiers
Local EPrints ID: 479428
URI: http://eprints.soton.ac.uk/id/eprint/479428
ISSN: 2327-4662
PURE UUID: 241b39c6-3acb-40b3-848c-4504f8aab787
Catalogue record
Date deposited: 24 Jul 2023 16:31
Last modified: 12 Dec 2024 02:32
Export record
Altmetrics
Contributors
Author:
Jiankang Zhang
Author:
Sheng Chen
Author:
Wei Koong Chai
Author:
Lajos Hanzo
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics