Statistical Modeling of Wall Roughness and Its Influence on NLOS VLC Channels in Underground Mining

This study investigates the impact of wall roughness on the performance of the Non-Line-of-Sight (NLOS) component in Visible Light Communication (VLC) systems designed for underground mining environments, adhering to safety and communication standards such as IEC 60079-28(intrinsic safety in explosive atmospheres) and IEEE 802.15.7 (VLC parameters). Using probabilistic models aligned with the ITU-R P.1238 propagation guidelines, the research evaluates how wall materials (e.g., coal, shale, limestone) and their irregular geometries, characterized by surface roughness profiles compliant with ISO 8503-2,influence reflection coefficients (0.05–0.85 range), incidence angles (0°–90°), and irradiance angles (5°–180°), which are critical for signal propagation. Simulation scenarios, parameterized with material reflectivity data from ASTM E423, explore the effects of statistical distributions (uniform, normal with μ = 0.3, σ = 0.2; exponential λ = 2; gamma α = 0.5, β = 0.2) on power distribution, channel impulse response, and reflection coefficients. The results indicate variations in maximum received power: a decrease of 80% for uniform distribution, an increase of 150% for exponential distribution, and a 100% increase for gamma distribution in reflection conditions. Under incidence and irradiance conditions, uniform distribution exhibited a 158.62% increase, whereas exponential distribution and gamma distribution experienced reductions of 72.22% and 7.04%, respectively. These variations align with IEC 62973-1 EMI limits and emphasize the role of roughness (Ra = 0.8–12.5 μm per ASME B46.1).

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Publication Details

Journal
Applied Sciences
Published
2025-02-22
DOI
https://doi.org/10.3390/app15052364
Citations
3
Primary Topic
Advanced Fiber Optic Sensors
Type
article
Field-Weighted Citation Impact
2.19

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article

Statistical Modeling of Wall Roughness and Its Influence on NLOS VLC Channels in Underground Mining

César A. Azurdia-Meza, Pablo Palacios Játiva, Iván Sánchez, Sebastian Cornejo
3 citations
Applied Sciences
Advanced Fiber Optic Sensors
2.19
article

Statistical Modeling of Wall Roughness and Its Influence on NLOS VLC Channels in Underground Mining

César A. Azurdia-Meza, Pablo Palacios Játiva, Iván Sánchez, Sebastian Cornejo
article en
3 citations

Abstract

This study investigates the impact of wall roughness on the performance of the Non-Line-of-Sight (NLOS) component in Visible Light Communication (VLC) systems designed for underground mining environments, adhering to safety and communication standards such as IEC 60079-28(intrinsic safety in explosive atmospheres) and IEEE 802.15.7 (VLC parameters). Using probabilistic models aligned with the ITU-R P.1238 propagation guidelines, the research evaluates how wall materials (e.g., coal, shale, limestone) and their irregular geometries, characterized by surface roughness profiles compliant with ISO 8503-2,influence reflection coefficients (0.05–0.85 range), incidence angles (0°–90°), and irradiance angles (5°–180°), which are critical for signal propagation. Simulation scenarios, parameterized with material reflectivity data from ASTM E423, explore the effects of statistical distributions (uniform, normal with μ = 0.3, σ = 0.2; exponential λ = 2; gamma α = 0.5, β = 0.2) on power distribution, channel impulse response, and reflection coefficients. The results indicate variations in maximum received power: a decrease of 80% for uniform distribution, an increase of 150% for exponential distribution, and a 100% increase for gamma distribution in reflection conditions. Under incidence and irradiance conditions, uniform distribution exhibited a 158.62% increase, whereas exponential distribution and gamma distribution experienced reductions of 72.22% and 7.04%, respectively. These variations align with IEC 62973-1 EMI limits and emphasize the role of roughness (Ra = 0.8–12.5 μm per ASME B46.1).

Applied SciencesVol. 15(5)
Universidad de Las Américas (EC), University of Chile (CL), Universidad Diego Portales (CL)
Comisión Nacional de Investigación Científica y Tecnológica
Openalex Percentile: Top 13%
Advanced Fiber Optic Sensors
2.19
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