| Autor: |
Chung, Wei-Yu, Shen, Li-Hsiang, Feng, Kai-Ten, Lin, Yuan-Chun, Lin, Shih-Cheng, Chang, Sheng-Fuh |
| Rok vydání: |
2023 |
| Předmět: |
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| Druh dokumentu: |
Working Paper |
| Popis: |
Channel State Information (CSI) is widely adopted as a feature for indoor localization. Taking advantage of the abundant information from the CSI, people can be accurately sensed even without equipped devices. However, the positioning error increases severely in non-line-of-sight (NLoS) regions. Reconfigurable intelligent surface (RIS) has been introduced to improve signal coverage in NLoS areas, which can re-direct and enhance reflective signals with massive meta-material elements. In this paper, we have proposed a Transformer-based RIS-assisted device-free sensing for joint people counting and localization (WiRiS) system to precisely predict the number of people and their corresponding locations through configuring RIS. A series of predefined RIS beams is employed to create inputs of fingerprinting CSI features as sequence-to-sequence learning database for Transformer. We have evaluated the performance of proposed WiRiS system in both ray-tracing simulators and experiments. Both simulation and real-world experiments demonstrate that people counting accuracy exceeds 90\%, and the localization error can achieve the centimeter-level, which outperforms the existing benchmarks without employment of RIS. |
| Databáze: |
arXiv |
| Externí odkaz: |
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