Low-Complexity Beamformer Design for Joint Radar and Communications Systems
Joint radar and communication (JRC) system is expected to significantly improve the utilization of spectrum resources, system performance, and reduce the equipment cost and size. In this letter, a JRC system containing a collocated multi-input multi-output (MIMO) radar and a multi-user communication...
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| Veröffentlicht in: | IEEE communications letters 2021-01, Vol.25 (1), p.259-263 |
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| creator | Dong, Fuwang Wang, Wei Hu, Ziying Hui, Tong |
| description | Joint radar and communication (JRC) system is expected to significantly improve the utilization of spectrum resources, system performance, and reduce the equipment cost and size. In this letter, a JRC system containing a collocated multi-input multi-output (MIMO) radar and a multi-user communication base station is considered, which can serve several downlink users and detect multiple targets simultaneously. The radar signal covariance matrix and the communication physical precoder are jointly designed by matching the desired beampattern for radar detection while maximizing the downlink communication signal to interference and noise ratio (SINR). By relaxing the original problems, the iterative process with closed-form expressions is proposed to obtain the sub-optimal solutions of the system. Compared with solving the optimization problems directly, the proposed algorithm can significantly reduce the computational complexity with a little loss of system performance. Finally, simulation results show the effectiveness of the proposed algorithm. |
| doi_str_mv | 10.1109/LCOMM.2020.3024574 |
| format | Article |
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In this letter, a JRC system containing a collocated multi-input multi-output (MIMO) radar and a multi-user communication base station is considered, which can serve several downlink users and detect multiple targets simultaneously. The radar signal covariance matrix and the communication physical precoder are jointly designed by matching the desired beampattern for radar detection while maximizing the downlink communication signal to interference and noise ratio (SINR). By relaxing the original problems, the iterative process with closed-form expressions is proposed to obtain the sub-optimal solutions of the system. Compared with solving the optimization problems directly, the proposed algorithm can significantly reduce the computational complexity with a little loss of system performance. Finally, simulation results show the effectiveness of the proposed algorithm.</description><identifier>ISSN: 1089-7798</identifier><identifier>EISSN: 1558-2558</identifier><identifier>DOI: 10.1109/LCOMM.2020.3024574</identifier><identifier>CODEN: ICLEF6</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Algorithms ; beamformer design ; Beamforming ; Communication ; Communications systems ; Complexity ; Covariance matrices ; Covariance matrix ; Downlink ; Downlinking ; Equipment costs ; Interference ; Iterative methods ; Joint radar and communication system ; MIMO communication ; MIMO radar ; multi-user communications ; Optimization ; Radar ; Radar antennas ; Radar detection ; Target detection</subject><ispartof>IEEE communications letters, 2021-01, Vol.25 (1), p.259-263</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2021</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c295t-6483640c3110b394aabd767aaf1cd053c174e50618d8f424fe624530b9fe36353</citedby><cites>FETCH-LOGICAL-c295t-6483640c3110b394aabd767aaf1cd053c174e50618d8f424fe624530b9fe36353</cites><orcidid>0000-0002-4392-1884 ; 0000-0001-6522-9082</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9201077$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27901,27902,54733</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/9201077$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Dong, Fuwang</creatorcontrib><creatorcontrib>Wang, Wei</creatorcontrib><creatorcontrib>Hu, Ziying</creatorcontrib><creatorcontrib>Hui, Tong</creatorcontrib><title>Low-Complexity Beamformer Design for Joint Radar and Communications Systems</title><title>IEEE communications letters</title><addtitle>LCOMM</addtitle><description>Joint radar and communication (JRC) system is expected to significantly improve the utilization of spectrum resources, system performance, and reduce the equipment cost and size. In this letter, a JRC system containing a collocated multi-input multi-output (MIMO) radar and a multi-user communication base station is considered, which can serve several downlink users and detect multiple targets simultaneously. The radar signal covariance matrix and the communication physical precoder are jointly designed by matching the desired beampattern for radar detection while maximizing the downlink communication signal to interference and noise ratio (SINR). By relaxing the original problems, the iterative process with closed-form expressions is proposed to obtain the sub-optimal solutions of the system. Compared with solving the optimization problems directly, the proposed algorithm can significantly reduce the computational complexity with a little loss of system performance. Finally, simulation results show the effectiveness of the proposed algorithm.</description><subject>Algorithms</subject><subject>beamformer design</subject><subject>Beamforming</subject><subject>Communication</subject><subject>Communications systems</subject><subject>Complexity</subject><subject>Covariance matrices</subject><subject>Covariance matrix</subject><subject>Downlink</subject><subject>Downlinking</subject><subject>Equipment costs</subject><subject>Interference</subject><subject>Iterative methods</subject><subject>Joint radar and communication system</subject><subject>MIMO communication</subject><subject>MIMO radar</subject><subject>multi-user communications</subject><subject>Optimization</subject><subject>Radar</subject><subject>Radar antennas</subject><subject>Radar detection</subject><subject>Target detection</subject><issn>1089-7798</issn><issn>1558-2558</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kMlOwzAQhi0EEqXwAnCxxDllvMX2EcJOqkosZ8tNHJSqiYudCvr2uLTiMJs0_ywfQucEJoSAviqL2XQ6oUBhwoByIfkBGhEhVEaTO0w5KJ1JqdUxOolxAQCKCjJCL6X_zgrfrZbupx02-MbZrvGhcwHfuth-9jhV-Nm3_YBfbW0Dtn2Nk6Bb921lh9b3Eb9t4uC6eIqOGruM7mwfx-jj_u69eMzK2cNTcV1mFdViyHKuWM6hYunyOdPc2nktc2ltQ6oaBKuI5E5ATlStGk554_L0EYO5bhzLmWBjdLmbuwr-a-3iYBZ-Hfq00lAuZTLGSeqiu64q-BiDa8wqtJ0NG0PAbKGZP2hmC83soSXRxU7UOuf-BZoCASnZLxKeZ1w</recordid><startdate>202101</startdate><enddate>202101</enddate><creator>Dong, Fuwang</creator><creator>Wang, Wei</creator><creator>Hu, Ziying</creator><creator>Hui, Tong</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>8FD</scope><scope>L7M</scope><orcidid>https://orcid.org/0000-0002-4392-1884</orcidid><orcidid>https://orcid.org/0000-0001-6522-9082</orcidid></search><sort><creationdate>202101</creationdate><title>Low-Complexity Beamformer Design for Joint Radar and Communications Systems</title><author>Dong, Fuwang ; Wang, Wei ; Hu, Ziying ; Hui, Tong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c295t-6483640c3110b394aabd767aaf1cd053c174e50618d8f424fe624530b9fe36353</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Algorithms</topic><topic>beamformer design</topic><topic>Beamforming</topic><topic>Communication</topic><topic>Communications systems</topic><topic>Complexity</topic><topic>Covariance matrices</topic><topic>Covariance matrix</topic><topic>Downlink</topic><topic>Downlinking</topic><topic>Equipment costs</topic><topic>Interference</topic><topic>Iterative methods</topic><topic>Joint radar and communication system</topic><topic>MIMO communication</topic><topic>MIMO radar</topic><topic>multi-user communications</topic><topic>Optimization</topic><topic>Radar</topic><topic>Radar antennas</topic><topic>Radar detection</topic><topic>Target detection</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Dong, Fuwang</creatorcontrib><creatorcontrib>Wang, Wei</creatorcontrib><creatorcontrib>Hu, Ziying</creatorcontrib><creatorcontrib>Hui, Tong</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><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>IEEE communications letters</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Dong, Fuwang</au><au>Wang, Wei</au><au>Hu, Ziying</au><au>Hui, Tong</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Low-Complexity Beamformer Design for Joint Radar and Communications Systems</atitle><jtitle>IEEE communications letters</jtitle><stitle>LCOMM</stitle><date>2021-01</date><risdate>2021</risdate><volume>25</volume><issue>1</issue><spage>259</spage><epage>263</epage><pages>259-263</pages><issn>1089-7798</issn><eissn>1558-2558</eissn><coden>ICLEF6</coden><abstract>Joint radar and communication (JRC) system is expected to significantly improve the utilization of spectrum resources, system performance, and reduce the equipment cost and size. In this letter, a JRC system containing a collocated multi-input multi-output (MIMO) radar and a multi-user communication base station is considered, which can serve several downlink users and detect multiple targets simultaneously. The radar signal covariance matrix and the communication physical precoder are jointly designed by matching the desired beampattern for radar detection while maximizing the downlink communication signal to interference and noise ratio (SINR). By relaxing the original problems, the iterative process with closed-form expressions is proposed to obtain the sub-optimal solutions of the system. Compared with solving the optimization problems directly, the proposed algorithm can significantly reduce the computational complexity with a little loss of system performance. Finally, simulation results show the effectiveness of the proposed algorithm.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/LCOMM.2020.3024574</doi><tpages>5</tpages><orcidid>https://orcid.org/0000-0002-4392-1884</orcidid><orcidid>https://orcid.org/0000-0001-6522-9082</orcidid></addata></record> |
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| ispartof | IEEE communications letters, 2021-01, Vol.25 (1), p.259-263 |
| issn | 1089-7798 1558-2558 |
| language | eng |
| recordid | cdi_ieee_primary_9201077 |
| source | IEEE Electronic Library (IEL) |
| subjects | Algorithms beamformer design Beamforming Communication Communications systems Complexity Covariance matrices Covariance matrix Downlink Downlinking Equipment costs Interference Iterative methods Joint radar and communication system MIMO communication MIMO radar multi-user communications Optimization Radar Radar antennas Radar detection Target detection |
| title | Low-Complexity Beamformer Design for Joint Radar and Communications Systems |
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