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Conference Paper: STARS Enabled Integrated Sensing and Communications
Title | STARS Enabled Integrated Sensing and Communications |
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Authors | |
Keywords | Cramer-Rao bound integrated sensing and communication (ISAC) simultaneously transmitting and reflecting intelligent surface (STARS) |
Issue Date | 2023 |
Citation | IEEE Transactions on Wireless Communications, 2023, v. 22, n. 10, p. 6750-6765 How to Cite? |
Abstract | A simultaneously transmitting and reflecting surface (STARS) enabled integrated sensing and communications (ISAC) framework is proposed, where the entire space is partitioned by STARS into a sensing space and a communication space. A novel sensing-at-STARS structure is proposed, where dedicated sensors are mounted at STARS to address the significant path loss and clutter interference of sensing. The Cramér-Rao bound (CRB) of the two-dimensional (2D) direction-of-arrivals (DOAs) estimation of the sensing target is derived, which is then minimized subject to the minimum communication requirement. A novel approach is proposed to transform the complicated CRB minimization problem into a trackable modified Fisher information matrix (FIM) optimization problem. Both independent and coupled phase-shift models of STARS are investigated: 1) For the independent phase-shift model, to address the coupling problem of ISAC waveform and STARS coefficient, an efficient double-loop iterative algorithm based on the penalty dual decomposition (PDD) framework is conceived; 2) For the coupled phase-shift model, based on the PDD framework, a low complexity alternating optimization algorithm is proposed to tackle the coupled phase-shift constraint by alternately optimizing the amplitude and phase-shift coefficients of STARS with closed-form expressions. Finally, the numerical results demonstrate that: 1) STARS significantly outperforms conventional RIS in terms of CRB under the communication constraints; 2) coupled phase-shift model achieves comparable performance to the independent one for low communication requirements or sufficient STARS elements; 3) it is more efficient to increase the number of passive elements of STARS than the active elements of the sensor; 4) higher sensing accuracy can be achieved by STARS using the practical 2D maximum likelihood estimator compared with the conventional RIS. |
Persistent Identifier | http://hdl.handle.net/10722/349875 |
ISSN | 2023 Impact Factor: 8.9 2023 SCImago Journal Rankings: 5.371 |
DC Field | Value | Language |
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dc.contributor.author | Wang, Zhaolin | - |
dc.contributor.author | Mu, Xidong | - |
dc.contributor.author | Liu, Yuanwei | - |
dc.date.accessioned | 2024-10-17T07:01:33Z | - |
dc.date.available | 2024-10-17T07:01:33Z | - |
dc.date.issued | 2023 | - |
dc.identifier.citation | IEEE Transactions on Wireless Communications, 2023, v. 22, n. 10, p. 6750-6765 | - |
dc.identifier.issn | 1536-1276 | - |
dc.identifier.uri | http://hdl.handle.net/10722/349875 | - |
dc.description.abstract | A simultaneously transmitting and reflecting surface (STARS) enabled integrated sensing and communications (ISAC) framework is proposed, where the entire space is partitioned by STARS into a sensing space and a communication space. A novel sensing-at-STARS structure is proposed, where dedicated sensors are mounted at STARS to address the significant path loss and clutter interference of sensing. The Cramér-Rao bound (CRB) of the two-dimensional (2D) direction-of-arrivals (DOAs) estimation of the sensing target is derived, which is then minimized subject to the minimum communication requirement. A novel approach is proposed to transform the complicated CRB minimization problem into a trackable modified Fisher information matrix (FIM) optimization problem. Both independent and coupled phase-shift models of STARS are investigated: 1) For the independent phase-shift model, to address the coupling problem of ISAC waveform and STARS coefficient, an efficient double-loop iterative algorithm based on the penalty dual decomposition (PDD) framework is conceived; 2) For the coupled phase-shift model, based on the PDD framework, a low complexity alternating optimization algorithm is proposed to tackle the coupled phase-shift constraint by alternately optimizing the amplitude and phase-shift coefficients of STARS with closed-form expressions. Finally, the numerical results demonstrate that: 1) STARS significantly outperforms conventional RIS in terms of CRB under the communication constraints; 2) coupled phase-shift model achieves comparable performance to the independent one for low communication requirements or sufficient STARS elements; 3) it is more efficient to increase the number of passive elements of STARS than the active elements of the sensor; 4) higher sensing accuracy can be achieved by STARS using the practical 2D maximum likelihood estimator compared with the conventional RIS. | - |
dc.language | eng | - |
dc.relation.ispartof | IEEE Transactions on Wireless Communications | - |
dc.subject | Cramer-Rao bound | - |
dc.subject | integrated sensing and communication (ISAC) | - |
dc.subject | simultaneously transmitting and reflecting intelligent surface (STARS) | - |
dc.title | STARS Enabled Integrated Sensing and Communications | - |
dc.type | Conference_Paper | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/TWC.2023.3245297 | - |
dc.identifier.scopus | eid_2-s2.0-85149373827 | - |
dc.identifier.volume | 22 | - |
dc.identifier.issue | 10 | - |
dc.identifier.spage | 6750 | - |
dc.identifier.epage | 6765 | - |
dc.identifier.eissn | 1558-2248 | - |