Fluid Antenna-Assisted Near-Field System
Fuente:
arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866910625406386176 |
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| author | Zhou, Jingxuan Yang, Yinchao Yang, Zhaohui Shikh-Bahaei, Mohammad |
| author_facet | Zhou, Jingxuan Yang, Yinchao Yang, Zhaohui Shikh-Bahaei, Mohammad |
| contents | This paper proposes a fluid antenna (FA)-assisted near-field integrated sensing and communications (ISAC) system enabled by the extremely large-scale simultaneously transmitting and reflecting surface (XL-STARS). By optimizing the communication beamformer, the sensing signal covariance matrix, the XL-STARS phase shift, and the FA position vector, the Cramér-Rao bound (CRB), as a metric for sensing performance, is minimized while ensuring the standard communication performance. A double-loop iterative algorithm based on the penalty dual decomposition (PDD) and block coordinate descent (BCD) methods is proposed to solve the non-convex minimization problem by decomposing it into three subproblems and optimizing the coupling variables for each subproblem iteratively. Simulation results validate the superior performance of the proposed algorithm. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_20472 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Fluid Antenna-Assisted Near-Field System Zhou, Jingxuan Yang, Yinchao Yang, Zhaohui Shikh-Bahaei, Mohammad Signal Processing This paper proposes a fluid antenna (FA)-assisted near-field integrated sensing and communications (ISAC) system enabled by the extremely large-scale simultaneously transmitting and reflecting surface (XL-STARS). By optimizing the communication beamformer, the sensing signal covariance matrix, the XL-STARS phase shift, and the FA position vector, the Cramér-Rao bound (CRB), as a metric for sensing performance, is minimized while ensuring the standard communication performance. A double-loop iterative algorithm based on the penalty dual decomposition (PDD) and block coordinate descent (BCD) methods is proposed to solve the non-convex minimization problem by decomposing it into three subproblems and optimizing the coupling variables for each subproblem iteratively. Simulation results validate the superior performance of the proposed algorithm. |
| title | Fluid Antenna-Assisted Near-Field System |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2409.20472 |