Phase Optimization and Message Passing Algorithm for RIS-Aided RSS Fingerprint Localization
The received signal strength (RSS) fingerprint-based technique is extensively utilized for indoor localization, as it does not require time synchronization. However, conventional RSS fingerprint localization schemes require multiple access points (APs), leading to a high deployment cost. In this wor...
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| Vydáno v: | IEEE transactions on vehicular technology Ročník 74; číslo 8; s. 12765 - 12775 |
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| Hlavní autoři: | , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
New York
IEEE
01.08.2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Témata: | |
| ISSN: | 0018-9545, 1939-9359 |
| On-line přístup: | Získat plný text |
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| Shrnutí: | The received signal strength (RSS) fingerprint-based technique is extensively utilized for indoor localization, as it does not require time synchronization. However, conventional RSS fingerprint localization schemes require multiple access points (APs), leading to a high deployment cost. In this work, by employing a reconfigurable intelligent surface (RIS), we propose an RSS fingerprint localization scheme with only one AP. First, we show that the variances of the measurement errors of RSSs in decibel (dB) are nonidentical (in contrast to the assumption of identical error variances in the literature), which needs to be considered in developing the localization scheme. Then, we optimize the phases of the RIS by minimizing the Cramér-Rao Lower Bound (CRLB) of localization with a particle swarm optimization (PSO) algorithm. To deal with the nonidentical measurement error variances, we develop a factor graph-based message passing localization algorithm by employing an approximate linear relationship between the target coordinates and the corresponding RSS. Numerical results are provided to demonstrate the effectiveness of the proposed method. We show that the proposed method outperforms existing schemes, and the optimization of RIS phases can significantly improve the localization performance. |
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| Bibliografie: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISSN: | 0018-9545 1939-9359 |
| DOI: | 10.1109/TVT.2025.3557922 |