Angle-of-Arrival (AOA) Visible Light Positioning (VLP) System Using Solar Cells With Third-Order Regression and Ridge Regression Algorithms

Hong, Chong-You; Wu, Yu-Chun; Liu, Yang; Chow, Chi‐Wai; Yeh, Chien‐Hung; Hsu, Ke-Ling; Lin, Dong-Chang; Liao, Xin-Lan; Lin, Kon‐Ping; Chen, Yiyuan

doi:10.1109/jphot.2020.2993031

Cited by 52 publications

(20 citation statements)

References 11 publications

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“…These techniques are divided into two classes of angulation and lateration. Angulation techniques, such as Angle Difference of Arrival (ADoA) [7] and Angle of Arrival (AoA) [8], measure the angles between the user and multiple VLC transmitters to estimate the location of the user. The lateration techniques, such as RSS and Time of Arrival (ToA), measure the distance between the user and multiple VLC transmitters to calculate the location of the user.It was shown in [10] that a combination of these techniques can improve the accuracy of VLC-based indoor localization.…”

Section: ) Indoor Localization In Vlc Systemsmentioning

confidence: 99%

Sub-Decimeter VLC 3D Indoor Localization With Handover Probability Analysis

Sheikholeslami

Fazel

Abouei³

et al. 2021

IEEE Access

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This paper addresses the problem of Visible Light Communication (VLC)-based indoor localization and handover, where mobile users communicate with hybrid VLC/mmWave Access Points (APs). The VLC system consists of multiple Light-Emitting Diodes (LEDs) treated as VLC transmitters, multiple Photodiodes (PDs) on the user's smart device, and multiple mmWave Radio Frequency (RF) transmitters used as complementary APs for the VLC system in the case of blockage. We propose a Convolutional Neural Network (CNN)-based algorithm consisting of offline and online modes. In the offline mode, we gather a data set by dividing the environment into fixed-sized elements where the received VLC signal along with the data attained from the smart device at each element represent a sample to train a CNN model for indoor localization. In the online mode, users employ the received VLC signals to estimate their locations. We then propose a virtual soft handover process according to the Coordinated Multiple Point (CoMP) transmission, where the HandOver Margin (HOM) and Waiting Time (WT) are dynamically set based on the change in Signal-to-Noise-Ratio (SNR) values in consecutive time slots. We derive a closed-form expression for the average effective throughput during the handover process, which shows the algorithm's superior performance compared to conventional soft and hard handovers. Simulation results show an average positioning error of 4.31 centimeters for the proposed localization algorithm in a 5 × 4 × 3 m 3 smart environment.

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Section: ) Indoor Localization In Vlc Systemsmentioning

confidence: 99%

Sub-Decimeter VLC 3D Indoor Localization With Handover Probability Analysis

Sheikholeslami

Fazel

Abouei³

et al. 2021

IEEE Access

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“…In [ 7 ], the authors combined machine learning with visible light and USES Angle of arrival for indoor targeting, and they ended up using quadrant solar cells as a way to increase progress. The literature [ 1 ] used improved reception devices, programmable beacons, and embedded positioning programs in smartphones to achieve simple and low-cost visible light indoor positioning.…”

Section: Related Workmentioning

confidence: 99%

“…Indoor positioning greatly expands the capabilities of these devices and therefore attracts a great amount of research work. The global positioning system has limitations in indoor positioning [5][6][7][8], and researchers have proposed the use of Wireless Fidelity (Wi-Fi), ultra-wideband (UWB), ultrasonic wave, and visible light positioning (VLP) technologies [9][10][11][12][13]. However, the main problem with Wi-Fi signals is the multipath effect.…”

Section: Introductionmentioning

confidence: 99%

Exploring Fast Fingerprint Construction Algorithm for Unmodulated Visible Light Indoor Localization

Shi

Niu

et al. 2020

Sensors

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The study of visible light indoor position has received considerable attention. The visible light indoor position has problems such as deployment difficulty and high cost. In our system, we propose a new fingerprint construction algorithm to simplify visible light indoor position. This method can realize the rapid construction of a visible fingerprint database and prove that the fingerprint database can be used repeatedly in different environments. We proved the theoretical feasibility of this method through theoretical derivation. We carried out extensive experiments in two classic real indoor environments. Experimental results show that reverse fingerprinting can be achieved. In 95% of cases, the positioning accuracy can be guaranteed to be less than 10 cm.

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“…However, TDOA requires clock synchronization of either the transmitter or the receiver, while TOA requires clock synchronization of both, which is hardly realized in a practical low-cost VLP system. Although the angle-of-arrival (AOA) [ 14 ] localization has no such requirement of clock synchronization, it typically needs a sensor array consisting of multiple PDs, cameras, or other hardware at the receiver side, which is also not suitable for very low-cost IoT applications. Additionally, the VLP system can also be achieved by using an image sensor (e.g., CMOS) as a receiver to derive the distance using the ratio of the LED size to its projection size [ 15 , 16 , 17 , 18 ], but cameras are normally high-cost and power-intensive and not suitable for low-power scenarios.…”

Section: Introductionmentioning

confidence: 99%

High-Accuracy Height-Independent 3D VLP Based on Received Signal Strength Ratio

Sun

et al. 2022

Sensors

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Visible light positioning (VLP) has attracted intensive attention from both academic and industrial communities thanks to its high accuracy, immunity to electromagnetic interference, and low deployment cost. In general, the receiver in a VLP system determines its own position by exploring the received signal strength (RSS) from the transmitter according to a pre-built RSS attenuation model. In such model-based methods, the LED’s emission power and the receiver’s height are usually required known and constant parameters to obtain reasonable positioning accuracy. However, the LED’s emission power is normally time-varying due to the fact that the LED’s optical output power is prone to changing with the LED’s temperature, and the receiver’s height is random in a realistic application scenario. To this end, we propose a height-independent three-dimensional (3D) VLP scheme based on the RSS ratio (RSSR), rather than only using RSS. Unlike existing RSS-based VLP methods, our method is able to independently find the horizontal coordinate, i.e., two-dimensional (2D) position, without a priori height information of the receiver, and also avoids the negative effect caused by fluctuation of the LED’s emission power. Moreover, we can further infer the height of the receiver to achieve three-dimensional (3D) positioning by iterating the 2D results back into positioning equations. To quickly verify the proposed scheme, we conduct theoretical analysis with mathematical proof and experimental results with real data, which confirm that the proposed scheme can achieve high position accuracy without known information of the receiver’s height and LED’s emission power. We also implement a VLP prototype with five LED transmitters, and experimental results show that the proposed scheme can achieve very low average errors of 2.73 cm in 2D and 7.20 cm in 3D.

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Angle-of-Arrival (AOA) Visible Light Positioning (VLP) System Using Solar Cells With Third-Order Regression and Ridge Regression Algorithms

Abstract: We put forward and demonstrate a angle-of-arrival (AOA) based visible-lightpositioning (VLP) system using quadrant-solar-cell (QSC) and third-order ridge regression machine learning (RRML) to improve the positioning accuracy.

Cited by 52 publications

References 11 publications

Sub-Decimeter VLC 3D Indoor Localization With Handover Probability Analysis

Sub-Decimeter VLC 3D Indoor Localization With Handover Probability Analysis

Exploring Fast Fingerprint Construction Algorithm for Unmodulated Visible Light Indoor Localization

High-Accuracy Height-Independent 3D VLP Based on Received Signal Strength Ratio

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