ISAC system assisted by RIS with sparse active elements

In this paper, we consider an integrated sensing and communications system assisted by a reconfigurable intelligent surface (RIS). A small number of sparsely placed active sensors are applied in the RIS to perform effective channels and, thereby, enable optimized beamforming for both communications...

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Vydáno v:	EURASIP journal on advances in signal processing Ročník 2023; číslo 1; s. 20 - 22
Hlavní autoři:	Asif Haider, Mirza, Zhang, Yimin D., Aboutanios, Elias
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Cham Springer International Publishing 01.12.2023 Springer Springer Nature B.V SpringerOpen
Témata:	Algorithms Beamforming Channels Communications systems Computer engineering Covariance matrix Credit unions Design Direction of arrival Direction-of-arrival estimation Engineering Integrated sensing and communications Intelligent reflecting surface Localization Optimization Propagation Quantum Information Technology Sensors Signal processing Signal Processing for Integrated Sensing and Communications Signal to noise ratio Signal,Image and Speech Processing Sparse array Spectrum allocation Spintronics Structured matrix completion Wireless communications Sparse array Intelligent reflecting surface Structured matrix completion Direction-of-arrival estimation Integrated sensing and communications
ISSN:	1687-6180, 1687-6172, 1687-6180
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Abstract	In this paper, we consider an integrated sensing and communications system assisted by a reconfigurable intelligent surface (RIS). A small number of sparsely placed active sensors are applied in the RIS to perform effective channels and, thereby, enable optimized beamforming for both communications and sensing objectives, namely, establishing reliable communication links with communication users (CUs) and effectively localize targets. The time-varying multipath channels between the RIS and the CU as well as the time-varying channel between the RIS and the targets are estimated by exploiting an interpolated Hermitian and Toeplitz covariance matrix followed by direction-of-arrival estimation using the MUSIC algorithm. Based on such results, we jointly optimize the transmit beamformer at the base station and the unit-modulus RIS passive beamformer. The RIS beamformer is optimized to maximize its minimum beam-pattern gain towards the desired sensing angles subject to the minimum signal-to-noise ratio requirement at the CU. Simulation results verify the effectiveness of the proposed approach, and the performance of different sparse array configurations is compared.
AbstractList	In this paper, we consider an integrated sensing and communications system assisted by a reconfigurable intelligent surface (RIS). A small number of sparsely placed active sensors are applied in the RIS to perform effective channels and, thereby, enable optimized beamforming for both communications and sensing objectives, namely, establishing reliable communication links with communication users (CUs) and effectively localize targets. The time-varying multipath channels between the RIS and the CU as well as the time-varying channel between the RIS and the targets are estimated by exploiting an interpolated Hermitian and Toeplitz covariance matrix followed by direction-of-arrival estimation using the MUSIC algorithm. Based on such results, we jointly optimize the transmit beamformer at the base station and the unit-modulus RIS passive beamformer. The RIS beamformer is optimized to maximize its minimum beam-pattern gain towards the desired sensing angles subject to the minimum signal-to-noise ratio requirement at the CU. Simulation results verify the effectiveness of the proposed approach, and the performance of different sparse array configurations is compared. Abstract In this paper, we consider an integrated sensing and communications system assisted by a reconfigurable intelligent surface (RIS). A small number of sparsely placed active sensors are applied in the RIS to perform effective channels and, thereby, enable optimized beamforming for both communications and sensing objectives, namely, establishing reliable communication links with communication users (CUs) and effectively localize targets. The time-varying multipath channels between the RIS and the CU as well as the time-varying channel between the RIS and the targets are estimated by exploiting an interpolated Hermitian and Toeplitz covariance matrix followed by direction-of-arrival estimation using the MUSIC algorithm. Based on such results, we jointly optimize the transmit beamformer at the base station and the unit-modulus RIS passive beamformer. The RIS beamformer is optimized to maximize its minimum beam-pattern gain towards the desired sensing angles subject to the minimum signal-to-noise ratio requirement at the CU. Simulation results verify the effectiveness of the proposed approach, and the performance of different sparse array configurations is compared.
ArticleNumber	20
Audience	Academic
Author	Asif Haider, Mirza Zhang, Yimin D. Aboutanios, Elias
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Snippet	In this paper, we consider an integrated sensing and communications system assisted by a reconfigurable intelligent surface (RIS). A small number of sparsely... Abstract In this paper, we consider an integrated sensing and communications system assisted by a reconfigurable intelligent surface (RIS). A small number of...
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SubjectTerms	Algorithms Beamforming Channels Communications systems Computer engineering Covariance matrix Credit unions Design Direction of arrival Direction-of-arrival estimation Engineering Integrated sensing and communications Intelligent reflecting surface Localization Optimization Propagation Quantum Information Technology Sensors Signal processing Signal Processing for Integrated Sensing and Communications Signal to noise ratio Signal,Image and Speech Processing Sparse array Spectrum allocation Spintronics Structured matrix completion Wireless communications
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Title	ISAC system assisted by RIS with sparse active elements
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