RIS-Assisted Near-Field ISAC for Multi-Target Indication in NLoS Scenarios
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arXiv
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| Autori principali: | , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866914031433940992 |
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| author | Ruan, Hang Nikbakht, Homa Zhang, Ruizhi Chen, Honglei Eldar, Yonina C. |
| author_facet | Ruan, Hang Nikbakht, Homa Zhang, Ruizhi Chen, Honglei Eldar, Yonina C. |
| contents | Enabling multi-target sensing in near-field integrated sensing and communication (ISAC) systems is a key challenge, particularly when line-of-sight paths are blocked. This paper proposes a beamforming framework that leverages a reconfigurable intelligent surface (RIS) to achieve multi-target indication. Our contribution is the extension of classic beampattern gain and inter-target cross-correlation metrics to the near-field, leveraging both angle and distance information to discriminate between multiple users and targets. We formulate a problem to maximize the worst-case sensing performance by jointly designing the beamforming at the base station and the phase shifts at the RIS, while guaranteeing communication rates. The non-convex problem is solved via an efficient alternating optimization (AO) algorithm that utilizes semidefinite relaxation (SDR). Simulations demonstrate that our RIS-assisted framework enables high-resolution sensing of co-angle targets in blocked scenarios. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_08642 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | RIS-Assisted Near-Field ISAC for Multi-Target Indication in NLoS Scenarios Ruan, Hang Nikbakht, Homa Zhang, Ruizhi Chen, Honglei Eldar, Yonina C. Signal Processing Enabling multi-target sensing in near-field integrated sensing and communication (ISAC) systems is a key challenge, particularly when line-of-sight paths are blocked. This paper proposes a beamforming framework that leverages a reconfigurable intelligent surface (RIS) to achieve multi-target indication. Our contribution is the extension of classic beampattern gain and inter-target cross-correlation metrics to the near-field, leveraging both angle and distance information to discriminate between multiple users and targets. We formulate a problem to maximize the worst-case sensing performance by jointly designing the beamforming at the base station and the phase shifts at the RIS, while guaranteeing communication rates. The non-convex problem is solved via an efficient alternating optimization (AO) algorithm that utilizes semidefinite relaxation (SDR). Simulations demonstrate that our RIS-assisted framework enables high-resolution sensing of co-angle targets in blocked scenarios. |
| title | RIS-Assisted Near-Field ISAC for Multi-Target Indication in NLoS Scenarios |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2509.08642 |