Visible light positioning in presence of malicious LED transmitters or intelligent reflecting surfaces

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Bilkent University
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Visible light positioning (VLP) is a recent solution to the localization problem in indoor environments which involves the use of light emitting diodes (LEDs) as transmitters and photodetectors (PDs) as receivers. VLP systems have in-creasingly been popular as LEDs are employed for illumination purposes over conventional light bulbs nowadays due to their various advantages. In this the-sis, we develop VLP algorithms for two main scenarios. In the first scenario, we assume that the system is not completely secure, meaning that the transmit power of some LEDs can be controlled by a third unknown party, i.e., hijacked, to degrade the positioning accuracy. In the second scenario, we assume the de-ployment of intelligent reflecting surfaces (IRSs) into the system to improve the positioning accuracy in the absence of line-of-sight (LOS) signals from of a subset of LED transmitters. First, we consider a VLP system in which a receiver performs position estimation based on signals emitted from a number of LED transmitters. Each LED transmitter can be malicious and transmit at an unknown power level with a certain probability. A maximum likelihood (ML) position estimator is derived based on the knowledge of probabilities that LED transmitters can be malicious. In addition, in the presence of training measurements, decision rules are designed for detection of malicious LED transmitters, and based on detection results, various ML based location estimators are proposed. To evaluate the performance of the proposed estimators, Cram´er-Rao lower bounds (CRLBs) are derived for position estimation in scenarios with and without a training phase. Moreover, an ML estimator is derived when the probabilities that the LED transmitters can be malicious are unknown. The performances of all the proposed estimators are evaluated via numerical examples and compared against the CRLBs. Second, we formulate and analyze a received power based position estimation problem for VLP systems in the presence of IRSs. In the proposed problem formulation, a visible light communication (VLC) receiver collects signals from a number of LED transmitters via LOS paths and/or via reflections from IRSs. We derive the CRLB expression and the ML estimator for generic three-dimensional positioning in the presence of IRSs with arbitrary configurations. In addition, we consider the problem of optimizing the orientations of IRSs when LOS paths are blocked, and propose an optimal adjustment approach for maximizing the received powers from IRSs based on analytic expressions, which can be solved in closed form or numerically. Since the optimal IRS orientations depend on the actual position of the VLC receiver, an N-step localization algorithm is proposed to perform adjustment of IRS orientations in the absence of any prior knowledge about the position of the VLC receiver. Performance of the proposed approach is evaluated via simulations and compared against the CRLB. It is deduced that although IRSs do no provide critical improvements in positioning accuracy in the presence of LOS signals from a sufficient number of LED transmitters, they can be very important in achieving accurate positioning when all or most of LOS paths are blocked.

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Visible light positioning (VLP), Estimation, Localization, Malicious LED transmitter, Cramer-Rao lower bound (CRLB), Intelligent reflecting surface (IRS), Reconfigurable intelligent surface (RIS)
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