Leveraging Large Reconfigurable Intelligent Surfaces as Anchors for Near-Field Positioning
Fuente:
arXiv
Salvato in:
| Autori principali: | , , |
|---|---|
| Natura: | Preprint |
| Pubblicazione: |
2025
|
| Soggetti: | |
| Accesso online: | |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866910951989575680 |
|---|---|
| author | Huang, Zeyu Rupp, Markus Schwarz, Stefan |
| author_facet | Huang, Zeyu Rupp, Markus Schwarz, Stefan |
| contents | In this work, we present a recent investigation on leveraging large reconfigurable intelligent surfaces (RIS) as anchors for positioning in wireless communication systems. Unlike existing approaches, we explicitly address the uncertainty arising from the substantial physical size of the RIS, particularly relevant when a user equipment resides in the near field, and propose a method that ensures accurate positioning under these conditions. We derive the corresponding Cramer-Rao bound for our scheme and validate the effectiveness of our scheme through numerical experiments, highlighting both the feasibility and potential of our approach. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_12730 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Leveraging Large Reconfigurable Intelligent Surfaces as Anchors for Near-Field Positioning Huang, Zeyu Rupp, Markus Schwarz, Stefan Emerging Technologies Information Theory In this work, we present a recent investigation on leveraging large reconfigurable intelligent surfaces (RIS) as anchors for positioning in wireless communication systems. Unlike existing approaches, we explicitly address the uncertainty arising from the substantial physical size of the RIS, particularly relevant when a user equipment resides in the near field, and propose a method that ensures accurate positioning under these conditions. We derive the corresponding Cramer-Rao bound for our scheme and validate the effectiveness of our scheme through numerical experiments, highlighting both the feasibility and potential of our approach. |
| title | Leveraging Large Reconfigurable Intelligent Surfaces as Anchors for Near-Field Positioning |
| topic | Emerging Technologies Information Theory |
| url | https://arxiv.org/abs/2505.12730 |