RACLN: Reconfigurable Intelligent Surface as Anchors for Cooperative Localization of Wireless Sensor Network

For future 6G systems, reconfigurable intelligent surface (RIS) controls phase shift of the reflective unit to improve the channel, which affects the received signal strength (RSS) of the microwave. In this article, we introduce the RIS as anchors into the cooperative localization wireless sensor ne...

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Bibliographic Details
Published in:IEEE internet of things journal 2024-09, Vol.11 (17), p.28824-28837
Main Authors: Lu, Ziyang, Zhao, Yubin, Ge, Yuming, Xu, Cheng-Zhong
Format: Article
Language:English
Subjects:
Algorithms
Cooperative localization
Cramér-Rao lower bound (CRLB)
Distance measurement
Genetic algorithms
Integer programming
Localization
Location awareness
Lower bounds
Millimeter wave technology
Nodes
Nonlinear control
Optimization
Phase control
Phase shift
Position errors
received signal strength (RSS)
reconfigurable intelligent surface (RIS)
Reconfigurable intelligent surfaces
semi-definite programming (SDP)
Semidefinite programming
Sensors
Signal strength
Wireless sensor networks
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Summary:For future 6G systems, reconfigurable intelligent surface (RIS) controls phase shift of the reflective unit to improve the channel, which affects the received signal strength (RSS) of the microwave. In this article, we introduce the RIS as anchors into the cooperative localization wireless sensor network (RACLN) to locate the sensor nodes. The RIS in RACLN can be a base station that provides multiple passive antennas for highly accurate localization. We derive the Cramér-Rao lower bound (CRLB) and the related squared position error bound (SPEB) for RACLN. The formulations indicate that the phase shift control of the RIS can improve the localization accuracy effectively. However, determining the appropriate phase shifts poses a nonlinear, nonconvex integer programming problem. Thus, we propose a semi-definite programming (SDP)-based phase optimization algorithm (SDP-PO) by relaxing the objective and achieving the minimum SPEB. Further, we also develop a low-complexity phase optimization (LC-PO) algorithm to reduce the dimension of the phase shift vector of SDP-PO. The simulation results demonstrate that the SPEB of RACLN is 94.68% smaller than the wireless sensor network using the sensor nodes as anchors. In addition, the proposed SDP-PO algorithms outperform the genetic algorithm (GA) and the alternate optimization (AO) with 17.12% and 37.49%.
ISSN:2327-4662
2327-4662
DOI:10.1109/JIOT.2024.3403972