Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/107151
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Electrical and Electronic Engineering | en_US |
dc.creator | Zhang, S | en_US |
dc.creator | Zhang, R | en_US |
dc.date.accessioned | 2024-06-13T01:04:13Z | - |
dc.date.available | 2024-06-13T01:04:13Z | - |
dc.identifier.issn | 1536-1276 | en_US |
dc.identifier.uri | http://hdl.handle.net/10397/107151 | - |
dc.language.iso | en | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers | en_US |
dc.rights | © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | en_US |
dc.rights | The following publication S. Zhang and R. Zhang, "Radio Map-Based 3D Path Planning for Cellular-Connected UAV," in IEEE Transactions on Wireless Communications, vol. 20, no. 3, pp. 1975-1989, March 2021 is available at https://doi.org/10.1109/TWC.2020.3037916. | en_US |
dc.subject | 3D path planning | en_US |
dc.subject | Cellular network | en_US |
dc.subject | Graph theory | en_US |
dc.subject | Radio map | en_US |
dc.subject | UAV communication | en_US |
dc.title | Radio map-based 3D path planning for cellular-connected UAV | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.spage | 1975 | en_US |
dc.identifier.epage | 1989 | en_US |
dc.identifier.volume | 20 | en_US |
dc.identifier.issue | 3 | en_US |
dc.identifier.doi | 10.1109/TWC.2020.3037916 | en_US |
dcterms.abstract | In this paper, we study the three-dimensional (3D) path planning for a cellular-connected unmanned aerial vehicle (UAV) to minimize its flying distance from given initial to final locations, while ensuring a target link quality in terms of the expected signal-to-interference-plus-noise ratio (SINR) at the UAV receiver with each of its associated ground base stations (GBSs) during the flight. To exploit the location-dependent and spatially varying channel as well as interference over the 3D space, we propose a new radio map based path planning framework for the UAV. Specifically, we consider the channel gain map of each GBS that provides its large-scale channel gains with uniformly sampled locations on a 3D grid, which are due to static and large-size obstacles (e.g., buildings) and thus assumed to be time-invariant. Based on the channel gain maps of GBSs as well as their loading factors, we then construct an SINR map that depicts the expected SINR levels over the sampled 3D locations. By leveraging the obtained SINR map, we proceed to derive the optimal UAV path by solving an equivalent shortest path problem (SPP) in graph theory. We further propose a grid quantization approach where the grid points in the SINR map are more coarsely sampled by exploiting the spatial channel/interference correlation over neighboring grids. Then, we solve an approximate SPP over the reduced-size SINR map (graph) with reduced complexity. Numerical results show that the proposed solution can effectively minimize the flying distance/time of the UAV subject to its communication quality constraint, and a flexible trade-off between performance and complexity can be achieved by adjusting the grid quantization ratio in the SINR map. Moreover, the proposed solution significantly outperforms various benchmark schemes without fully exploiting the channel/interference spatial distribution in the network. | en_US |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | IEEE transactions on wireless communications, Mar. 2021, v. 20, no. 3, p. 1975-1989 | en_US |
dcterms.isPartOf | IEEE transactions on wireless communications | en_US |
dcterms.issued | 2021-03 | - |
dc.identifier.scopus | 2-s2.0-85097203860 | - |
dc.description.validate | 202403 bckw | en_US |
dc.description.oa | Accepted Manuscript | en_US |
dc.identifier.FolderNumber | EIE-0262 | - |
dc.description.fundingSource | Self-funded | en_US |
dc.description.pubStatus | Published | en_US |
dc.identifier.OPUS | 43363397 | - |
dc.description.oaCategory | Green (AAM) | en_US |
Appears in Collections: | Journal/Magazine Article |
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File | Description | Size | Format | |
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Zhang_Radio_Map_Based.pdf | Pre-Published version | 6.18 MB | Adobe PDF | View/Open |
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