Quasi-Passive Indoor Optical Wireless Communication Systems

Wang, Ke

doi:10.1109/lpt.2020.3026343

Cited by 6 publications

(2 citation statements)

References 16 publications

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“…Figure 4(a) represents the updated four different clusters and their centers. Currently, 49 users are in four groups of 16,10,11,12 and they belong to their designated clusters 0,1,2, and 3 in ascending order. In Figure 4(b), centroids are updated from five to four after executing the K-means clustering.…”

Section: K-means Clusteringmentioning

confidence: 99%

An integrated machine learning model for indoor network optimization to maximize coverage

Reza

Rifat²,

Ahmed³

2021

IJEECS

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Indoor network optimization is not a simple task due to the obstacles, interference, and attenuation of the signal in an environment. Intense noises can affect the intelligibility of the signal and reduce the coverage strength significantly which results in a poor user experience. Most of the existing works are associated with finding the location of the devices via different mathematical and generic algorithmic approaches, but very few are focused on implying machine learning algorithms. The purpose of this research is to introduce an integrated machine learning model to find maximum indoor coverage with a minimum number of transmitters. The users in the indoor environment also have been allocated based on the most reliable signal strength and the system is also capable of allocating new users. K-means clustering, K-nearest neighbor (KNN), support vector machine (SVM), and Gaussian Naïve Bayes (GNB) have been used to provide an optimized solution. It is found that KNN, SVM, and GNB obtained maximum accuracy of 100% in some cases. However, among all the algorithms, KNN performed the best and provided an average accuracy of 93.33%. K-fold cross-validation (Kf-CV) technique has been added to validate the experimental simulations and re-evaluate the outcomes of the machine learning models.

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Section: K-means Clusteringmentioning

confidence: 99%

An integrated machine learning model for indoor network optimization to maximize coverage

Reza

Rifat²,

Ahmed³

2021

IJEECS

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“…In these systems, FSO communication using near-infrared laser light is more suitable for mobile access than traditional radio frequency (RF) and visible light communication using illumination systems because of several advantages such as broad bandwidth, license-free bandwidth, eyesafe wavelength, connectivity with optical fiber networks in buildings, and privacy protection [1], [3]- [9]. Considering such mobile optical communication systems, laser safety regulations will prohibit FSO signal transmission with high enough power to fully cover the user area using a single spreading light [8]. Therefore, to maintain a constant connection with the moving users, optical signal-pointing technology using optical beam scanning devices is required, in addition to user-localized and tracking technologies using RF and image-sensing systems [1].…”

Section: Introductionmentioning

confidence: 99%

Broadband Port-Selective Silicon Beam Scanning Device for Free-Space Optical Communication

Akizuki¹,

Yoshida²,

Matsumoto³

et al. 2023

IEICE Trans. Electron.

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Indoor free space optical (FSO) communication technology that provides high-speed connectivity to edge users is expected to be introduced in the near future mobile communication system, where the silicon photonics solid-state beam scanning device is a promising tool because of its low cost, long-term reliability, and other beneficial properties. However, the current two-dimensional beam scanning devices using grating coupler arrays have difficulty in increasing the transmission capacity because of bandwidth regulation. To solve the problem, we have introduced a broadband surface optical coupler, "elephant coupler," which has great potential for combining wavelength and spatial division multiplexing technologies into the beam scanning device, as an alternative to grating couplers. The prototype port-selective silicon beam scanning device fabricated using a 300 mm CMOS pilot line achieved broadband optical beam emission with a 1 dB-loss bandwidth of 40 nm and demonstrated beam scanning using an imaging lens. The device has also exhibited free-space signal transmission of non-return-to-zero on-off-keying signals at 10 Gbps over a wide wavelength range of 60 nm. In this paper, we present an overview of the developed beam scanning device. Furthermore, the theoretical design guidelines for indoor mobile FSO communication are discussed.

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A survey of optical wireless technologies: practical considerations, impairments, security issues and future research directions

et al. 2022

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Quasi-Passive Indoor Optical Wireless Communication Systems

Cited by 6 publications

References 16 publications

An integrated machine learning model for indoor network optimization to maximize coverage

An integrated machine learning model for indoor network optimization to maximize coverage

Broadband Port-Selective Silicon Beam Scanning Device for Free-Space Optical Communication

A survey of optical wireless technologies: practical considerations, impairments, security issues and future research directions

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