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On the Performance Gain of Integrated Sensing and Communications: A Subspace Correlation Perspective
In this paper, we shed light on the performance gain of integrated sensing and communications (ISAC) from the perspective of channel correlations between radar sensing and communication (S&C), namely ISAC subspace correlation. To begin with, we consider a multi-input multi-output (MIMO) ISAC sys...
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creator | Lu, Shihang Meng, Xiao Du, Zhen Xiong, Yifeng Liu, Fan |
description | In this paper, we shed light on the performance gain of integrated sensing and communications (ISAC) from the perspective of channel correlations between radar sensing and communication (S&C), namely ISAC subspace correlation. To begin with, we consider a multi-input multi-output (MIMO) ISAC system and reveal that the optimal ISAC signal is in the subspace spanned by the transmitted steering vectors of the sensing channel and the right singular matrix of the communication channel. By leveraging this result, we study a basic ISAC scenario with a single target and a single-antenna communication user, and derive the optimal waveform covariance matrix for minimizing the estimation error under a given communication rate constraint. To quantify the integration gain of ISAC systems, we define the subspace "correlation coefficient" to characterize the coupling effect between S&C channels. Finally, numerical results are provided to validate the effectiveness of the proposed approaches. |
doi_str_mv | 10.1109/ICC45041.2023.10279428 |
format | conference_proceeding |
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To begin with, we consider a multi-input multi-output (MIMO) ISAC system and reveal that the optimal ISAC signal is in the subspace spanned by the transmitted steering vectors of the sensing channel and the right singular matrix of the communication channel. By leveraging this result, we study a basic ISAC scenario with a single target and a single-antenna communication user, and derive the optimal waveform covariance matrix for minimizing the estimation error under a given communication rate constraint. To quantify the integration gain of ISAC systems, we define the subspace "correlation coefficient" to characterize the coupling effect between S&C channels. Finally, numerical results are provided to validate the effectiveness of the proposed approaches.</description><identifier>EISSN: 1938-1883</identifier><identifier>EISBN: 1538674629</identifier><identifier>EISBN: 9781538674628</identifier><identifier>DOI: 10.1109/ICC45041.2023.10279428</identifier><language>eng</language><publisher>IEEE</publisher><subject>Closed-form solutions ; Communication channels ; Correlation ; Correlation coefficient ; Integrated sensing and communications ; integration gain ; Performance gain ; Radar ; signal processing ; Simulation ; waveform optimization</subject><ispartof>ICC 2023 - IEEE International Conference on Communications, 2023, p.2735-2740</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/10279428$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,776,780,785,786,23910,23911,25119,27904,54533,54910</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/10279428$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Lu, Shihang</creatorcontrib><creatorcontrib>Meng, Xiao</creatorcontrib><creatorcontrib>Du, Zhen</creatorcontrib><creatorcontrib>Xiong, Yifeng</creatorcontrib><creatorcontrib>Liu, Fan</creatorcontrib><title>On the Performance Gain of Integrated Sensing and Communications: A Subspace Correlation Perspective</title><title>ICC 2023 - IEEE International Conference on Communications</title><addtitle>ICC</addtitle><description>In this paper, we shed light on the performance gain of integrated sensing and communications (ISAC) from the perspective of channel correlations between radar sensing and communication (S&C), namely ISAC subspace correlation. To begin with, we consider a multi-input multi-output (MIMO) ISAC system and reveal that the optimal ISAC signal is in the subspace spanned by the transmitted steering vectors of the sensing channel and the right singular matrix of the communication channel. By leveraging this result, we study a basic ISAC scenario with a single target and a single-antenna communication user, and derive the optimal waveform covariance matrix for minimizing the estimation error under a given communication rate constraint. To quantify the integration gain of ISAC systems, we define the subspace "correlation coefficient" to characterize the coupling effect between S&C channels. Finally, numerical results are provided to validate the effectiveness of the proposed approaches.</description><subject>Closed-form solutions</subject><subject>Communication channels</subject><subject>Correlation</subject><subject>Correlation coefficient</subject><subject>Integrated sensing and communications</subject><subject>integration gain</subject><subject>Performance gain</subject><subject>Radar</subject><subject>signal processing</subject><subject>Simulation</subject><subject>waveform optimization</subject><issn>1938-1883</issn><isbn>1538674629</isbn><isbn>9781538674628</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2023</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNo1kN1KwzAcxaMguE3fQCQv0JnvJt6NorMwmDC9Hmny74ysaUk6wbe3fl0czoHD-V0chG4pWVJKzF1dVUISQZeMML6khJVGMH2G5lRyrUqhmDlHM2q4LqjW_BLNc34nRDLD6Qz5bcTjG-BnSG2fOhsd4LUNEfctruMIh2RH8HgHMYd4wDZ6XPVdd4rB2TH0Md_jFd6dmjzYaVn1KcHxp_gm5gHcGD7gCl209pjh-s8X6PXx4aV6KjbbdV2tNkVgRIwFb6VUhMoWlHGGEOdtM6lkZcM0AeVAAvWMCemsFKqdote0EcIb1RDF-ALd_HIDAOyHFDqbPvf_l_AvWIdXBA</recordid><startdate>20230528</startdate><enddate>20230528</enddate><creator>Lu, Shihang</creator><creator>Meng, Xiao</creator><creator>Du, Zhen</creator><creator>Xiong, Yifeng</creator><creator>Liu, Fan</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>20230528</creationdate><title>On the Performance Gain of Integrated Sensing and Communications: A Subspace Correlation Perspective</title><author>Lu, Shihang ; Meng, Xiao ; Du, Zhen ; Xiong, Yifeng ; Liu, Fan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i204t-3f556015fe69c900cdabcda727b280e6ce5e1d2245ca546fd22d81b44d96b0623</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Closed-form solutions</topic><topic>Communication channels</topic><topic>Correlation</topic><topic>Correlation coefficient</topic><topic>Integrated sensing and communications</topic><topic>integration gain</topic><topic>Performance gain</topic><topic>Radar</topic><topic>signal processing</topic><topic>Simulation</topic><topic>waveform optimization</topic><toplevel>online_resources</toplevel><creatorcontrib>Lu, Shihang</creatorcontrib><creatorcontrib>Meng, Xiao</creatorcontrib><creatorcontrib>Du, Zhen</creatorcontrib><creatorcontrib>Xiong, Yifeng</creatorcontrib><creatorcontrib>Liu, Fan</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Lu, Shihang</au><au>Meng, Xiao</au><au>Du, Zhen</au><au>Xiong, Yifeng</au><au>Liu, Fan</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>On the Performance Gain of Integrated Sensing and Communications: A Subspace Correlation Perspective</atitle><btitle>ICC 2023 - IEEE International Conference on Communications</btitle><stitle>ICC</stitle><date>2023-05-28</date><risdate>2023</risdate><spage>2735</spage><epage>2740</epage><pages>2735-2740</pages><eissn>1938-1883</eissn><eisbn>1538674629</eisbn><eisbn>9781538674628</eisbn><abstract>In this paper, we shed light on the performance gain of integrated sensing and communications (ISAC) from the perspective of channel correlations between radar sensing and communication (S&C), namely ISAC subspace correlation. To begin with, we consider a multi-input multi-output (MIMO) ISAC system and reveal that the optimal ISAC signal is in the subspace spanned by the transmitted steering vectors of the sensing channel and the right singular matrix of the communication channel. By leveraging this result, we study a basic ISAC scenario with a single target and a single-antenna communication user, and derive the optimal waveform covariance matrix for minimizing the estimation error under a given communication rate constraint. To quantify the integration gain of ISAC systems, we define the subspace "correlation coefficient" to characterize the coupling effect between S&C channels. Finally, numerical results are provided to validate the effectiveness of the proposed approaches.</abstract><pub>IEEE</pub><doi>10.1109/ICC45041.2023.10279428</doi><tpages>6</tpages></addata></record> |
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subjects | Closed-form solutions Communication channels Correlation Correlation coefficient Integrated sensing and communications integration gain Performance gain Radar signal processing Simulation waveform optimization |
title | On the Performance Gain of Integrated Sensing and Communications: A Subspace Correlation Perspective |
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