CandlES

Rahaim, Michael; Borogovac, Tarik; Carruthers, Jeffrey B.

doi:10.1145/1860079.1860082

Cited by 34 publications

(4 citation statements)

References 5 publications

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“…Moreover, it offers the possibility to import a variety of LED lamps in illuminating engineering society (IES) format and can serve as a tool for simulation and planning of VLP systems [272]. Finally, CandLES® simulates VLC and lighting systems, assessing illumination coverage and error rate, and it allows system components to be modeled and integrated into a larger model [273].…”

Section: F Propagation Model(s)mentioning

confidence: 99%

Visible Light Positioning as a Next-Generation Indoor Positioning Technology: A Tutorial

Bastiaens,

Alijani,

Joseph

et al. 2024

IEEE Commun. Surv. Tutorials

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Indoor positioning technology has become undisputedly pervasive in modern society. It can be used for numerous applications in various environments, ranging from agriculture to smart industry. Among the different indoor positioning technologies, the development of the indoor visible light positioning (VLP) system has gained momentum recently thanks to its low cost and centimetre-order accuracy. Moreover, VLP is a promising candidate technology for integration with Light Fidelity (Li-Fi), which relies on the optical spectrum to build future wireless networks and plays a significant role in sixth-generation (6G) wireless networks. This tutorial investigates VLP as a novel positioning technology in depth. The inherent characteristics and fundamentals of this technology are extensively described with the components of a VLP system and possible localization approaches being discussed. Furthermore, a mathematical and technical discussion of a simple minimum retrofit of the single photodiode (PD) received signal strength (RSS) VLP systems is provided. Finally, the paper concludes with open challenges and a future roadmap for VLP.

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Section: F Propagation Model(s)mentioning

confidence: 99%

Visible Light Positioning as a Next-Generation Indoor Positioning Technology: A Tutorial

Bastiaens,

Alijani,

Joseph

et al. 2024

IEEE Commun. Surv. Tutorials

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“…Hammouda et al [81] perform a two-step resource allocation process to allocate both zone and user level resources evaluating ASE and fairness. They study their system performance in a room-scale transmission scenario using the simulation tool CandLES [82]. However, they assume fixed receiver orientation.…”

Section: Managing System Dynamicsmentioning

confidence: 99%

Interference in multi-user optical wireless communications systems

Abdalla

Rahaim

Little

2020

Phil. Trans. R. Soc. A.

Self Cite

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Visible light communications (VLC) (including LiFi) represent a subset of the broader field of optical wireless communications. Where narrow beams, typical of free space optical communications are largely free from interference. VLC encompasses use cases involving combined illumination and data access and supporting a wireless access point (AP) model. The use of many units provides scaling of spatial coverage for both lighting and data access. However, AP replication in close proximity creates many interference challenges that motivate the investigation embodied in this paper. In particular, we frame the interference challenge in the context of existing strategies for driving improvements in link performance and consider the impacts of multiple users, multiple sources and multiple cells. Lastly, we review the state of existing research in this area and recommend areas for further study. This article is part of the theme issue ‘Optical wireless communication’.

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“…For this dataset, we have used the Communication and Lighting Emulation Software (CandLES) [30], which allowed us to calculate RSS values and other features, such as the channel impulse response, h(t), in a VLC network. This software implements a fast multi-receiver channel estimation for indoor optical wireless communications [31].…”

Section: Vlc Datasetmentioning

confidence: 99%

A Simple Indoor Localization Methodology for Fast Building Classification Models Based on Fingerprints

et al. 2019

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Indoor localization has received tremendous attention in the last two decades due to location-aware services being highly demanded. Wireless networks have been suggested to solve this problem in many research works, and efficient algorithms have been developed with precise location and high accuracy. Nevertheless, those approaches often have high computational and high energy consumption. Hence, in temporary environments, such as emergency situations, where a fast deployment of an indoor localization system is required, those methods are not appropriate. In this manuscript, a methodology for fast building of an indoor localization system is proposed. For that purpose, a reduction of the data dimensionality is achieved by applying data fusion and feature transformation, which allow us to reduce the computational cost of the classifier training phase. In order to validate the methodology, three different datasets were used: two of them are public datasets based mainly on Received Signal Strength (RSS) from different Wi-Fi access point, and the third is a set of RSS values gathered from the LED lamps in a Visible Light Communication (VLC) network. The simulation results show that the proposed methodology considerably amends the overall computational performance and provides an acceptable location estimation error.

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CandlES

Cited by 34 publications

References 5 publications

Visible Light Positioning as a Next-Generation Indoor Positioning Technology: A Tutorial

Visible Light Positioning as a Next-Generation Indoor Positioning Technology: A Tutorial

Interference in multi-user optical wireless communications systems

A Simple Indoor Localization Methodology for Fast Building Classification Models Based on Fingerprints

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