Placement Optimization of UAV-Mounted Mobile Base Stations
In terrestrial communication networks without fixed infrastructure, unmanned aerial vehicle-mounted mobile base stations (MBSs) provide an efficient solution to achieve wireless connectivity. This letter aims to minimize the number of MBSs needed to provide wireless coverage for a group of distribut...
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Veröffentlicht in: | IEEE communications letters 2017-03, Vol.21 (3), p.604-607 |
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creator | Lyu, Jiangbin Zeng, Yong Zhang, Rui Lim, Teng Joon |
description | In terrestrial communication networks without fixed infrastructure, unmanned aerial vehicle-mounted mobile base stations (MBSs) provide an efficient solution to achieve wireless connectivity. This letter aims to minimize the number of MBSs needed to provide wireless coverage for a group of distributed ground terminals (GTs), ensuring that each GT is within the communication range of at least one MBS. We propose a polynomial-time algorithm with successive MBS placement, where the MBSs are placed sequentially starting on the area perimeter of the uncovered GTs along a spiral path toward the center, until all GTs are covered. Numerical results show that the proposed algorithm performs favorably compared with other schemes in terms of the number of required MBSs as well as time complexity. |
doi_str_mv | 10.1109/LCOMM.2016.2633248 |
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This letter aims to minimize the number of MBSs needed to provide wireless coverage for a group of distributed ground terminals (GTs), ensuring that each GT is within the communication range of at least one MBS. We propose a polynomial-time algorithm with successive MBS placement, where the MBSs are placed sequentially starting on the area perimeter of the uncovered GTs along a spiral path toward the center, until all GTs are covered. 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This letter aims to minimize the number of MBSs needed to provide wireless coverage for a group of distributed ground terminals (GTs), ensuring that each GT is within the communication range of at least one MBS. We propose a polynomial-time algorithm with successive MBS placement, where the MBSs are placed sequentially starting on the area perimeter of the uncovered GTs along a spiral path toward the center, until all GTs are covered. Numerical results show that the proposed algorithm performs favorably compared with other schemes in terms of the number of required MBSs as well as time complexity.</description><subject>Base stations</subject><subject>Clustering algorithms</subject><subject>geometric disk cover problem</subject><subject>Heuristic algorithms</subject><subject>mobile base station placement</subject><subject>Mobile communication</subject><subject>Partitioning algorithms</subject><subject>Spirals</subject><subject>Unmanned aerial vehicles</subject><subject>user coverage</subject><subject>Wireless communication</subject><issn>1089-7798</issn><issn>1558-2558</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9j81Kw0AUhQdRsFZfQDd5gdR753_c1WJVaIigdRsmkxuIpE3JxIU-vekPbu65i_Md-Bi7RZghgrtfLfIsm3FAPeNaCC7tGZugUjbl4zkff7AuNcbZS3YV4xcAWK5wwh7eWh9oQ9shyXdDs2l-_dB026Srk_X8M8267-1AVZJ1ZdNS8ugjJe_DoRKv2UXt20g3p5yy9fLpY_GSrvLn18V8lQZh-ZDK0lpJpqzJuArK4ACkCCr4WptKuwq9NJpQYa2wgsBVKQ1y7QzKINxoM2X8uBv6Lsae6mLXNxvf_xQIxd6-ONgXe_viZD9Cd0eoIaJ_wBjNQQnxBymaVTQ</recordid><startdate>201703</startdate><enddate>201703</enddate><creator>Lyu, Jiangbin</creator><creator>Zeng, Yong</creator><creator>Zhang, Rui</creator><creator>Lim, Teng Joon</creator><general>IEEE</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><orcidid>https://orcid.org/0000-0001-5609-7647</orcidid><orcidid>https://orcid.org/0000-0002-3670-0434</orcidid></search><sort><creationdate>201703</creationdate><title>Placement Optimization of UAV-Mounted Mobile Base Stations</title><author>Lyu, Jiangbin ; Zeng, Yong ; Zhang, Rui ; Lim, Teng Joon</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c382t-4b884e7bfe79d0bc90043c5caf67d69d1a476e151f51d0c25b471269714c39263</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Base stations</topic><topic>Clustering algorithms</topic><topic>geometric disk cover problem</topic><topic>Heuristic algorithms</topic><topic>mobile base station placement</topic><topic>Mobile communication</topic><topic>Partitioning algorithms</topic><topic>Spirals</topic><topic>Unmanned aerial vehicles</topic><topic>user coverage</topic><topic>Wireless communication</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lyu, Jiangbin</creatorcontrib><creatorcontrib>Zeng, Yong</creatorcontrib><creatorcontrib>Zhang, Rui</creatorcontrib><creatorcontrib>Lim, Teng Joon</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><jtitle>IEEE communications letters</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Lyu, Jiangbin</au><au>Zeng, Yong</au><au>Zhang, Rui</au><au>Lim, Teng Joon</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Placement Optimization of UAV-Mounted Mobile Base Stations</atitle><jtitle>IEEE communications letters</jtitle><stitle>COML</stitle><date>2017-03</date><risdate>2017</risdate><volume>21</volume><issue>3</issue><spage>604</spage><epage>607</epage><pages>604-607</pages><issn>1089-7798</issn><eissn>1558-2558</eissn><coden>ICLEF6</coden><abstract>In terrestrial communication networks without fixed infrastructure, unmanned aerial vehicle-mounted mobile base stations (MBSs) provide an efficient solution to achieve wireless connectivity. This letter aims to minimize the number of MBSs needed to provide wireless coverage for a group of distributed ground terminals (GTs), ensuring that each GT is within the communication range of at least one MBS. We propose a polynomial-time algorithm with successive MBS placement, where the MBSs are placed sequentially starting on the area perimeter of the uncovered GTs along a spiral path toward the center, until all GTs are covered. Numerical results show that the proposed algorithm performs favorably compared with other schemes in terms of the number of required MBSs as well as time complexity.</abstract><pub>IEEE</pub><doi>10.1109/LCOMM.2016.2633248</doi><tpages>4</tpages><orcidid>https://orcid.org/0000-0001-5609-7647</orcidid><orcidid>https://orcid.org/0000-0002-3670-0434</orcidid></addata></record> |
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subjects | Base stations Clustering algorithms geometric disk cover problem Heuristic algorithms mobile base station placement Mobile communication Partitioning algorithms Spirals Unmanned aerial vehicles user coverage Wireless communication |
title | Placement Optimization of UAV-Mounted Mobile Base Stations |
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