Radio Tomographic Imaging with Reconfigurable Intelligent Surfaces
Radio tomographic imaging (RTI) is a device-free sensing technology that can image the radio frequency (RF) attenuation of physical objects in the environment. RTI uses received signal strength (RSS) information from a wireless communication network (WCN) to perform image reconstruction. However it...
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Published in | IEEE transactions on wireless communications p. 1 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
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31.07.2024
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Abstract | Radio tomographic imaging (RTI) is a device-free sensing technology that can image the radio frequency (RF) attenuation of physical objects in the environment. RTI uses received signal strength (RSS) information from a wireless communication network (WCN) to perform image reconstruction. However it requires a dense WCN consisting of a large number of nodes making it difficult to apply in realistic WCN. In this paper we investigate the performance of RTI when reconfigurable intelligent surfaces (RISs) are integrated into the WCN for integrated sensing and communication (ISAC). This approach can potentially enable the use of RTI in realistic WCN without a large number of nodes. Theoretical and numerical comparisons based on the Cramér-Rao Lower Bound (CRLB) are provided to verify the improvement on sensing performance brought by RIS. The scaling behavior of the reconstruction error as a function of the number of RIS element groups is also derived. Simulations are conducted to validate the proposed RIS-RTI system with a limited number of nodes. The results indicate that incorporating RIS can reduce the necessary number of nodes by more than a half while maintaining high-quality reconstruction compared to a network without RIS. |
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AbstractList | Radio tomographic imaging (RTI) is a device-free sensing technology that can image the radio frequency (RF) attenuation of physical objects in the environment. RTI uses received signal strength (RSS) information from a wireless communication network (WCN) to perform image reconstruction. However it requires a dense WCN consisting of a large number of nodes making it difficult to apply in realistic WCN. In this paper we investigate the performance of RTI when reconfigurable intelligent surfaces (RISs) are integrated into the WCN for integrated sensing and communication (ISAC). This approach can potentially enable the use of RTI in realistic WCN without a large number of nodes. Theoretical and numerical comparisons based on the Cramér-Rao Lower Bound (CRLB) are provided to verify the improvement on sensing performance brought by RIS. The scaling behavior of the reconstruction error as a function of the number of RIS element groups is also derived. Simulations are conducted to validate the proposed RIS-RTI system with a limited number of nodes. The results indicate that incorporating RIS can reduce the necessary number of nodes by more than a half while maintaining high-quality reconstruction compared to a network without RIS. |
Author | Dubey, Amartansh Kundu, Neel Kanth Rao, Junhui Li, Zan Shen, Shanpu Murch, Ross |
Author_xml | – sequence: 1 givenname: Zan orcidid: 0000-0003-3053-7741 surname: Li fullname: Li, Zan organization: Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong, China – sequence: 2 givenname: Amartansh orcidid: 0000-0002-1726-9802 surname: Dubey fullname: Dubey, Amartansh organization: Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong, China – sequence: 3 givenname: Shanpu orcidid: 0000-0001-8487-2903 surname: Shen fullname: Shen, Shanpu organization: Department of Electrical Engineering and Electronics, University of Liverpool, Liverpool, U.K – sequence: 4 givenname: Neel Kanth orcidid: 0000-0002-6439-4024 surname: Kundu fullname: Kundu, Neel Kanth organization: Centre for Applied Research in Electronics, Indian Institute of Technology Delhi, New Delhi, India – sequence: 5 givenname: Junhui orcidid: 0000-0001-6247-3223 surname: Rao fullname: Rao, Junhui organization: Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong, China – sequence: 6 givenname: Ross orcidid: 0000-0002-2527-7693 surname: Murch fullname: Murch, Ross organization: Department of Electronic and Computer Engineering and the Institute for Advanced Study, The Hong Kong University of Science and Technology, Hong Kong, China |
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SubjectTerms | Accuracy Device-free sensing Image reconstruction Radio links radio tomographic imaging reconfigurable intelligent surface Scattering Tomography Wireless communication wireless sensor network Wireless sensor networks |
Title | Radio Tomographic Imaging with Reconfigurable Intelligent Surfaces |
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