@inproceedings{dcfb58b5059b4637b3e6e264f6d12c08,
title = "BEAMFORMING DESIGN AND PERFORMANCE EVALUATION FOR RIS-AIDED LOCALIZATION USING LEO SATELLITE SIGNALS",
abstract = "The growing availability of low-Earth orbit (LEO) satellites, coupled with the anticipated widespread deployment of reconfigurable intelligent surfaces (RISs), opens up promising prospects for new localization paradigms. This paper studies RIS-aided localization using LEO satellite signals. The Cram{\'e}r-Rao bound of the considered localization problem is derived, based on which an optimal RIS beamforming design that minimizes the derived bound is proposed. Numerical results demonstrate the superiority of the proposed beamforming scheme over benchmark alternatives, while also revealing that the synergy between LEO satellites and RISs holds the promise for localization.",
keywords = "beamforming, Cram{\'e}r-Rao bound, LEO satellite, localization, reconfigurable intelligent surfaces",
author = "Lei Wang and Pinjun Zheng and Xing Liu and Tarig Ballal and Al-Naffouri, {Tareq Y.}",
note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 49th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2024 ; Conference date: 14-04-2024 Through 19-04-2024",
year = "2024",
doi = "10.1109/ICASSP48485.2024.10446090",
language = "English (US)",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "13166--13170",
booktitle = "2024 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2024 - Proceedings",
address = "United States",
}