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Efficient near-field localization aided with reconfigurable intelligent surface using geometric dilution of precision
- Source :
- Journal of Information and Telecommunication, Vol 8, Iss 2, Pp 208-230 (2024)
- Publication Year :
- 2024
- Publisher :
- Taylor & Francis Group, 2024.
-
Abstract
- ABSTRACTReconfigurable intelligent surfaces (RISs) are anticipated to constitute a critical component of forthcoming communication networks due to their ability to establish controllable wireless environments. Furthermore, RIS can be leveraged to solve infeasible localization problems. This paper presents a novel adoption of the geometric dilution of precision (GDoP) analysis in the design of non-line of sight (NLoS) single anchor millimetre wave (mmWave) large RIS-aided localization in the near-field. Considering downlink transmission, the time difference of arrival (TDoA) is used to estimate the positioning by extracting the signal contribution of each RIS tile. Considering the enriched time of arrival (ToA) measurements provided by RIS, the RIS tiles involved in TDoA-based estimation should be selected properly. Therefore, the GDoP adopted in this context is to select RIS tile combinations that achieve minimum GDoP values. It has been shown via numerical simulation that the proposed design of the RIS-aided localization outperforms other state-of-the-art techniques that adopt the signal-to-noise ratio (SNR) for the selection of the RIS tiles. It is demonstrated that the proposed scheme can provide sufficient localization accuracy involving only 10% of RIS tiles, whereas the SNR method requires about (70–80) % of the tiles to approximately achieve the same accuracy.
Details
- Language :
- English
- ISSN :
- 24751839 and 24751847
- Volume :
- 8
- Issue :
- 2
- Database :
- Directory of Open Access Journals
- Journal :
- Journal of Information and Telecommunication
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.29091652344e6d9d0d01ff11b6af78
- Document Type :
- article
- Full Text :
- https://doi.org/10.1080/24751839.2023.2272488