A Fingerprint Database Generation Method for RIS-Assisted Indoor Positioning
Xin Cheng, Yu He, Menglu Li, Ruoguang Li, Feng Shu, and Guangjie Han

TL;DR
This paper introduces a novel open-source method for generating realistic RIS-assisted RSS fingerprint databases for indoor positioning, addressing the challenge of accurate channel modeling and spatial consistency.
Contribution
It proposes a comprehensive RIS-assisted channel modeling approach, including a sorting algorithm, phase configuration strategy, and mutual coupling modeling, to improve fingerprint database accuracy.
Findings
Enhanced fingerprint database realism demonstrated through simulations
Improved localization accuracy with proposed phase configuration strategy
Insights into system design from positioning performance analysis
Abstract
Reconfigurable intelligent surface (RIS) has emerged as a promising technology to enhance indoor wireless communication and sensing performance. However, the construction of reliable received signal strength (RSS)-based fingerprint databases for RIS-assisted indoor positioning remains an open challenge due to the lack of realistic and spatially consistent channel modeling methods. In this paper, we propose a novel method with open-source code for generating RIS-assisted RSS fingerprint databases. Our method captures the complex RIS-assisted multipath behaviors by extended cluster-based channel modeling and the physical and electromagnetic properties of RIS and transmitter (Tx). And the spatial consistency is incorporated when simulating the fingerprint data collection across neighboring positions. Moreover, an effective sorting algorithm is proposed to solve the online synchronization…
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Taxonomy
TopicsAdvanced Wireless Communication Technologies · Indoor and Outdoor Localization Technologies · Underwater Vehicles and Communication Systems
