UAV Placement for VR Reconstruction: A Tradeoff Between Resolution and Delay

Tang, XW; Huang, Y; Shi, Y; Huang, XL; Yu, S

UAV Placement for VR Reconstruction: A Tradeoff Between Resolution and Delay

Tang, XW Huang, Y Shi, Y Huang, XL Yu, S

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Publisher:: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Publication Type:: Journal Article
Citation:: IEEE Communications Letters, 2023, 27, (5), pp. 1382-1386
Issue Date:: 2023-05-01

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Field	Value	Language
dc.contributor.author	Tang, XW
dc.contributor.author	Huang, Y
dc.contributor.author	Shi, Y
dc.contributor.author	Huang, XL
dc.contributor.author	Yu, S https://orcid.org/0000-0003-4485-6743
dc.date.accessioned	2024-03-13T03:32:58Z
dc.date.available	2024-03-13T03:32:58Z
dc.date.issued	2023-05-01
dc.identifier.citation	IEEE Communications Letters, 2023, 27, (5), pp. 1382-1386
dc.identifier.issn	1089-7798
dc.identifier.issn	1558-2558
dc.identifier.uri	http://hdl.handle.net/10453/176623
dc.description.abstract	Unmanned aerial vehicle (UAV) can be combined with virtual reality (VR) to collect the rapidly changing physical environment by leveraging its high flexibility, so as to provide an immersive experience for metaverse users. In this letter, we study the UAV placement problem in UAV-assisted VR systems where UAVs are deployed to capture images of ground targets and then transmit them to ground users for virtual environment reconstruction. The goal is to minimize the transmission delay while satisfying the image resolution requirement. Firstly, the UAV placement problem is formulated into a non-convex optimization problem. Then, an efficient algorithm is proposed to obtain a high-quality solution by adopting the block coordinate descent and successive convex approximation techniques with low complexity. Finally, the numerical results are provided and show that considerable benefits can be obtained with a suboptimal UAV placement. Specifically, the proposed scheme can reduce the transmission delay by over 15 ms compared to the conventional scheme when the received signal-to-noise ratio at the reference distance is 106 and the resolution requirement is 0.5.
dc.language	English
dc.publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.relation.ispartof	IEEE Communications Letters
dc.relation.isbasedon	10.1109/LCOMM.2023.3261917
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0805 Distributed Computing, 0906 Electrical and Electronic Engineering, 1005 Communications Technologies
dc.subject.classification	Networking & Telecommunications
dc.subject.classification	4006 Communications engineering
dc.subject.classification	4009 Electronics, sensors and digital hardware
dc.subject.classification	4606 Distributed computing and systems software
dc.title	UAV Placement for VR Reconstruction: A Tradeoff Between Resolution and Delay
dc.type	Journal Article
utslib.citation.volume	27
utslib.for	0805 Distributed Computing
utslib.for	0906 Electrical and Electronic Engineering
utslib.for	1005 Communications Technologies
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	University of Technology Sydney/Strength - CCSP - Centre for Cyber Security and Privacy
utslib.copyright.status	closed_access	*
dc.date.updated	2024-03-13T03:32:57Z
pubs.issue	5
pubs.publication-status	Published
pubs.volume	27
utslib.citation.issue	5

Abstract:

Unmanned aerial vehicle (UAV) can be combined with virtual reality (VR) to collect the rapidly changing physical environment by leveraging its high flexibility, so as to provide an immersive experience for metaverse users. In this letter, we study the UAV placement problem in UAV-assisted VR systems where UAVs are deployed to capture images of ground targets and then transmit them to ground users for virtual environment reconstruction. The goal is to minimize the transmission delay while satisfying the image resolution requirement. Firstly, the UAV placement problem is formulated into a non-convex optimization problem. Then, an efficient algorithm is proposed to obtain a high-quality solution by adopting the block coordinate descent and successive convex approximation techniques with low complexity. Finally, the numerical results are provided and show that considerable benefits can be obtained with a suboptimal UAV placement. Specifically, the proposed scheme can reduce the transmission delay by over 15 ms compared to the conventional scheme when the received signal-to-noise ratio at the reference distance is 106 and the resolution requirement is 0.5.

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http://hdl.handle.net/10453/176623