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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Veröffentlicht in:IEEE transactions on vehicular technology Jg. 74; H. 8; S. 12765 - 12775
Hauptverfasser: Wang, Man, Jin, Ming, Guo, Qinghua, Li, Wenjuan
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.08.2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Algorithms
Decibels
factor graph
Fingerprint recognition
Fingerprints
Localization
Location awareness
Lower bounds
Measurement errors
Message passing
Optimization
Particle swarm optimization
received signal strength (RSS)
reconfigurable intelligent surface (RIS)
Reconfigurable intelligent surfaces
Reflection
Signal processing algorithms
Signal strength
Synchronization
Target localization
Time synchronization
Training
Vectors
Wireless communication
ISSN:0018-9545, 1939-9359
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Zusammenfassung: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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ISSN:0018-9545
1939-9359
DOI:10.1109/TVT.2025.3557922