TR2023-142
RIS-Assisted Joint Preamble Detection and Localization
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- "RIS-Assisted Joint Preamble Detection and Localization", IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), DOI: 10.1109/CAMSAP58249.2023.10403493, December 2023.BibTeX TR2023-142 PDF
- @inproceedings{Nuti2023dec,
- author = {Nuti, Pooja and Kim, Kyeong Jin and Wang, Pu and Koike-Akino, Toshiaki and Parsons, Kieran},
- title = {RIS-Assisted Joint Preamble Detection and Localization},
- booktitle = {IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)},
- year = 2023,
- month = dec,
- doi = {10.1109/CAMSAP58249.2023.10403493},
- isbn = {979-8-3503-4453-0},
- url = {https://www.merl.com/publications/TR2023-142}
- }
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- "RIS-Assisted Joint Preamble Detection and Localization", IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), DOI: 10.1109/CAMSAP58249.2023.10403493, December 2023.
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Research Areas:
Abstract:
Reconfigurable intelligent surface (RIS) is envisioned to be a key enabling technology for future wireless systems and is currently being developed and studied for various applications. In this work, we investigate how a single, passive RIS can assist both preamble detection and localization. We propose a joint preamble detection and localization scheme and a rule-based multi-antenna peak correction method to improve the reliability of range estimates and preamble detection. The proposed approach builds prior information on a low-speed factory vehicle’s position based on a previously estimated position to more efficiently estimate the vehicle’s current location along a trajectory. Simulation results present how RIS can enable these two tasks and how performance varies across various vehicle positions.