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Efficient deployment of UAV-powered sensors for optimal coverage and connectivity

Efficient deployment of UAV-powered sensors for optimal coverage and connectivity
Efficient deployment of UAV-powered sensors for optimal coverage and connectivity
The Internet of Things (IoT) digitizes the physical world with wireless devices sensing their surroundings and delivering periodic notifications of parameters they are monitoring. However, this operation is bound by finite-capacity batteries, in which replenishment is practically infeasible due to the envisioned size of the IoT networks. By also considering the autonomous and self-sufficient service vision of the IoT paradigm, the need for novel approaches overcoming the energy constraints is evident. Here, unmanned aerial vehicles (UAVs) come into prominence. The UAVs can remotely energize wireless devices, via wireless power transfer (WPT), and thus guarantee reliable sensing coverage as well as longevity in the IoT domain. However, this can be only achieved by the precise alignment of both UAVs and wireless devices. Thus, this paper presents an efficient deployment strategy based on the circle packing problem, in which a lower-bound for the required number of wireless devices achieving optimal coverage is derived. The analysis, based on empirical measurements, reveals the design considerations for an energy harvesting (EH)-aided UAV scenario with regard to Federal Communications Commission (FCC) regulations, power consumption of wireless devices, and reporting frequency requirements of the IoT applications. Our results elaborate on a number of trade-offs, based on UAV, device, and medium characteristics, and provide realistic guidelines, achieving optimal coverage while meeting application requirements.
IEEE
Cetinkaya, Oktay
6cb457a5-77b8-415d-b524-9e8728c35f0a
Merrett, Geoff
89b3a696-41de-44c3-89aa-b0aa29f54020
Cetinkaya, Oktay
6cb457a5-77b8-415d-b524-9e8728c35f0a
Merrett, Geoff
89b3a696-41de-44c3-89aa-b0aa29f54020

Cetinkaya, Oktay and Merrett, Geoff (2020) Efficient deployment of UAV-powered sensors for optimal coverage and connectivity. In IEEE Wireless Communications and Networking Conference (WCNC) '20. IEEE. 6 pp . (In Press)

Record type: Conference or Workshop Item (Paper)

Abstract

The Internet of Things (IoT) digitizes the physical world with wireless devices sensing their surroundings and delivering periodic notifications of parameters they are monitoring. However, this operation is bound by finite-capacity batteries, in which replenishment is practically infeasible due to the envisioned size of the IoT networks. By also considering the autonomous and self-sufficient service vision of the IoT paradigm, the need for novel approaches overcoming the energy constraints is evident. Here, unmanned aerial vehicles (UAVs) come into prominence. The UAVs can remotely energize wireless devices, via wireless power transfer (WPT), and thus guarantee reliable sensing coverage as well as longevity in the IoT domain. However, this can be only achieved by the precise alignment of both UAVs and wireless devices. Thus, this paper presents an efficient deployment strategy based on the circle packing problem, in which a lower-bound for the required number of wireless devices achieving optimal coverage is derived. The analysis, based on empirical measurements, reveals the design considerations for an energy harvesting (EH)-aided UAV scenario with regard to Federal Communications Commission (FCC) regulations, power consumption of wireless devices, and reporting frequency requirements of the IoT applications. Our results elaborate on a number of trade-offs, based on UAV, device, and medium characteristics, and provide realistic guidelines, achieving optimal coverage while meeting application requirements.

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Accepted/In Press date: 15 January 2020
Venue - Dates: IEEE Wireless Communications and Networking Conference: Beyond Connectivity: What Comes After 5G, Korea, Republic of, 2020-04-06 - 2020-04-09

Identifiers

Local EPrints ID: 437512
URI: http://eprints.soton.ac.uk/id/eprint/437512
PURE UUID: e93a2258-e1b5-48c5-a27e-0a8f3187e7ec
ORCID for Geoff Merrett: ORCID iD orcid.org/0000-0003-4980-3894

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Date deposited: 03 Feb 2020 17:30
Last modified: 09 Jun 2020 00:29

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Contributors

Author: Oktay Cetinkaya
Author: Geoff Merrett ORCID iD

University divisions

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