A GBSM Indoor Channel Model With an Arbitrary Center Point of Gaussian Scatterer Distribution

Tennakoon, Priyashantha; Wavegedara, Chandika B.

doi:10.1109/tap.2021.3119036

Cited by 2 publications

(3 citation statements)

References 17 publications

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“…Due to the model's spatial-temporal properties, in terms of the arrival angle and arrival time [41], it will eventually be possible to apply it to multipath wireless communication systems. Tennskoon [44] proposed a three-dimensional (3D) stochastic geometry model with a Gaussian distribution centred on an arbitrary point within a sphere.…”

Section: Work On Scattering Distribution Patternsmentioning

confidence: 99%

A New COVID-19 Detection Method Based on CSK/QAM Visible Light Communication and Machine Learning

Soto

Zamorano-Illanes

Becerra

et al. 2023

Sensors

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This article proposes a novel method for detecting coronavirus disease 2019 (COVID-19) in an underground channel using visible light communication (VLC) and machine learning (ML). We present mathematical models of COVID-19 Deoxyribose Nucleic Acid (DNA) gene transfer in regular square constellations using a CSK/QAM-based VLC system. ML algorithms are used to classify the bands present in each electrophoresis sample according to whether the band corresponds to a positive, negative, or ladder sample during the search for the optimal model. Complexity studies reveal that the square constellation N=22i×22i,(i=3) yields a greater profit. Performance studies indicate that, for BER = 10−3, there are gains of −10 [dB], −3 [dB], 3 [dB], and 5 [dB] for N=22i×22i,(i=0,1,2,3), respectively. Based on a total of 630 COVID-19 samples, the best model is shown to be XGBoots, which demonstrated an accuracy of 96.03%, greater than that of the other models, and a recall of 99% for positive values.

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Section: Work On Scattering Distribution Patternsmentioning

confidence: 99%

A New COVID-19 Detection Method Based on CSK/QAM Visible Light Communication and Machine Learning

Soto

Zamorano-Illanes

Becerra

et al. 2023

Sensors

View full text Add to dashboard Cite

show abstract

“…Several works related to scattering distribution models applied to general communication schemes are presented in [ 13 , 14 , 15 , 16 , 17 ]. In [ 13 , 14 ], a uniform distribution model that locates the scatterers in a 2D disk region centered on the optical receiver is presented.…”

Section: Introductionmentioning

confidence: 99%

“…The demonstrated statistical results are presented in terms of arrival angle and arrival time. Finally, the work in [ 17 ] proposes a general channel model for any communication system that includes scattering particles. This three-dimensional model is based on stochastic geometry, where a Gaussian distribution of scatterers located around an arbitrary point within a spheroid is assumed.…”

Section: Introductionmentioning

confidence: 99%

An Enhanced VLC Channel Model for Underground Mining Environments Considering a 3D Dust Particle Distribution Model

Játiva

Azurdia-Meza

Sánchez

et al. 2022

Sensors

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Underground Mining (UM) is a hostile industry that generally requires a wireless communication system as a cross-cutting axis for its optimal operation. Therefore, in the last five years, it has been shown that, in addition to radio-frequency-based communication links, wireless optical communications, such as Visible Light Communication (VLC), can be applied to UM environments. The application of VLC systems in underground mines, known as UM-VLC, must take into account the unique physical features of underground mines. Among the physical phenomena found in underground mines, the most important ones are the positioning of optical transmitters and receivers, irregular walls, shadowing, and a typical phenomenon found in tunnels known as scattering, which is caused by the atmosphere and dust particles. Consequently, it is necessary to use proper dust particle distribution models consistent with these scenarios to describe the scattering phenomenon in a coherent way in order to design realistic UM-VLC systems with better performance. Therefore, in this article, we present an in-depth study of the interaction of optical links with dust particles suspended in the UM environment and the atmosphere. In addition, we analytically derived a hemispherical 3D dust particle distribution model, along with its main statistical parameters. This analysis allows to develop a more realistic scattering channel component and presents an enhanced UM-VLC channel model. The performance of the proposed UM-VLC system is evaluated using computational numerical simulations following the IEEE 802.1.5.7 standard in terms of Channel Impulse Response (CIR), received power, Signal-to-Noise-Ratio (SNR), Root Mean Square (RMS) delay spread, and Bit Error Rate (BER). The results demonstrate that the hemispherical dust particle distribution model is more accurate and realistic in terms of the metrics evaluated compared to other models found in the literature. Furthermore, the performance of the UM-VLC system is negatively affected when the number of dust particles suspended in the environment increases.

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A GBSM Indoor Channel Model With an Arbitrary Center Point of Gaussian Scatterer Distribution

Cited by 2 publications

References 17 publications

A New COVID-19 Detection Method Based on CSK/QAM Visible Light Communication and Machine Learning

A New COVID-19 Detection Method Based on CSK/QAM Visible Light Communication and Machine Learning

An Enhanced VLC Channel Model for Underground Mining Environments Considering a 3D Dust Particle Distribution Model

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