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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Veröffentlicht in:EURASIP journal on advances in signal processing Jg. 2023; H. 1; S. 20 - 22
Hauptverfasser: Asif Haider, Mirza, Zhang, Yimin D., Aboutanios, Elias
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Cham Springer International Publishing 01.12.2023
Springer
Springer Nature B.V
SpringerOpen
Schlagworte:
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
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung: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.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:1687-6180
1687-6172
1687-6180
DOI:10.1186/s13634-023-00977-5