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Coverage optimization for UAV-aided Internet of Things with partial channel knowledge
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Wang, Xuanxuan, Feng, Wei, Chen, Yunfei and Ge, Ning (2018) Coverage optimization for UAV-aided Internet of Things with partial channel knowledge. Journal of Communications and Information Networks, 3 (4). pp. 55-63. doi:10.1007/s41650-018-0039-9
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WRAP-coverage-optimization-UAV-aided-Internet-Things-partial-channel-knowledge-Chen-2018.pdf - Accepted Version - Requires a PDF viewer. Download (1366Kb) | Preview |
Official URL: https://doi.org/10.1007/s41650-018-0039-9
Abstract
Due to the high maneuverability of unmanned aerial vehicles (UAVs), they have been widely deployed to boost the performance of Internet of Things (IoT). In this paper, to promote the coverage performance of UAV-aided IoT communications, we maximize the minimum average rate of the IoT devices by jointly optimizing the resource allocation strategy and the UAV altitude. Particularly, to depict the practical propagation environment, we take the composite channel model including both the small-scale and the large-scale channel fading into account. Due to the difficulty in acquiring the random small-scale channel fading, we assume that only the large-scale channel sate information (CSI) is available. On this basis, we formulate an optimization problem, which is not convex and challenging to solve. Then, an efficient iterative algorithm is proposed using block coordinate descent and successive convex optimization tools. Finally, simulation results are presented to demonstrate the significant performance gain of the proposed scheme over existing ones.
| Item Type: | Journal Article | ||||||
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| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering T Technology > TL Motor vehicles. Aeronautics. Astronautics |
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| Divisions: | Faculty of Science > Engineering | ||||||
| Library of Congress Subject Headings (LCSH): | Internet of things , Drone aircraft , Wireless communication system | ||||||
| Journal or Publication Title: | Journal of Communications and Information Networks | ||||||
| Publisher: | Springer | ||||||
| ISSN: | 2096-1081 | ||||||
| Official Date: | 29 December 2018 | ||||||
| Dates: |
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| Volume: | 3 | ||||||
| Number: | 4 | ||||||
| Page Range: | pp. 55-63 | ||||||
| DOI: | 10.1007/s41650-018-0039-9 | ||||||
| Status: | Peer Reviewed | ||||||
| Publication Status: | Published | ||||||
| Publisher Statement: | This is a post-peer-review, pre-copyedit version of an article published in Journal of Communications and Information Networks. The final authenticated version is available online at:https://doi.org/10.1007/s41650-018-0039-9 | ||||||
| Access rights to Published version: | Restricted or Subscription Access | ||||||
| Funder: | Beijing Natural Science Foundation (BNSF), Guo jia zi ran ke xue ji jin wei yuan hui (China) [National Science Foundation of China (NSFC)] | ||||||
| Grant number: | L172041 (BNSF), 61701457 (NSFC), 61771286 (NSFC), 91638205 (NSFC), 61671478 (NSFC), 61621091 (NSFC) |
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