Signal Attenuation Prediction Model for a 22 GHz Terrestrial Communication Link in Sudan Due to Dust and Sand Storms Using Machine Learning

Shamim, Mohammed Zubair M.; Elsheikh, Elfatih A. A.; Suliman, F. M.; Islam, Md. Rafiqul

doi:10.1109/access.2021.3132700

Cited by 8 publications

(2 citation statements)

References 15 publications

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“…In [184], a machine learning (ML) model based on the Extra Trees Regressor method is presented that estimates the EM wave attenuation due to SDS. The model employs visibility, temperature, relative humidity, atmospheric pressure, and wind speed to forecast attenuation for a 22 GHz link in the region of Sudan.…”

Section: G Ai Based Methodsmentioning

confidence: 99%

Earth and Martian Sand and Dust Storms: A Comprehensive Review of Attenuation Modelling and Measurements

Noreen,

Giannetti,

Lottici

2024

IEEE Access

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Sand and dust storms (SDS) are significant atmospheric phenomena that have a negative impact on wireless links operating at various frequencies. Specifically, sand and dust (SD) particles produce attenuation in propagating electromagnetic (EM) waves upon impact, which must be measured for the proper functioning of the fade mitigation strategy. The attenuation due to SDS can be reliably evaluated using specialized equipment. However, field experiments have been conducted in only a few locations and for a limited number of link geometries; therefore, the results are not immediately generalizable to all locations. Consequently, various attenuation models based on accessible meteorological data have been developed to provide sufficient inputs for system margin calculations under all environmental conditions. In this paper, we present a comprehensive review of an extensive set of Earth SDS attenuation models that differ based on various particle characteristics in terrestrial and space communication. Furthermore, we discuss how variables such as humidity and surface charges carried by the particles are addressed in the literature. We also provide the results of various field studies conducted in many parts of the world under diverse conditions to directly measure the influence of SDS on wireless communication systems. Dust is also a significant meteorological factor in the Martian atmosphere, where it affects the efficiency of the wireless sensor networks used by NASA's Mars Exploration Project. We explore how attenuation has been extrapolated in the Martian atmosphere. Additionally, we discuss future research challenges in SDS.INDEX TERMS Attenuation, Mie Scattering, Rayleigh Model, Sand and dust storm (SDS), Satellite communication.

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Section: G Ai Based Methodsmentioning

confidence: 99%

Earth and Martian Sand and Dust Storms: A Comprehensive Review of Attenuation Modelling and Measurements

Noreen,

Giannetti,

Lottici

2024

IEEE Access

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“…The most endangered region of Sudan prone to the risks of desertification lies between 12°and 18°N, near its capital-Khartoum. The flat topography of the country exacerbates the desertification problems and increases the effects of dust and sand storms that often occur in the northern regions of Sudan [56][57][58][59]. Specifically, this includes the effects of the creeping sands and dunes from the areas of Sahara, Nubian and Libyan deserts, as can be seen in Figure 1.…”

Section: Study Areamentioning

confidence: 99%

Multispectral Satellite Image Analysis for Computing Vegetation Indices by R in the Khartoum Region of Sudan, Northeast Africa

Lemenkova

Debeir

2023

J. Imaging

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Desertification is one of the most destructive climate-related issues in the Sudan–Sahel region of Africa. As the assessment of desertification is possible by satellite image analysis using vegetation indices (VIs), this study reports on the technical advantages and capabilities of scripting the ‘raster’ and ‘terra’ R-language packages for computing the VIs. The test area which was considered includes the region of the confluence between the Blue and White Niles in Khartoum, southern Sudan, northeast Africa and the Landsat 8–9 OLI/TIRS images taken for the years 2013, 2018 and 2022, which were chosen as test datasets. The VIs used here are robust indicators of plant greenness, and combined with vegetation coverage, are essential parameters for environmental analytics. Five VIs were calculated to compare both the status and dynamics of vegetation through the differences between the images collected within the nine-year span. Using scripts for computing and visualising the VIs over Sudan demonstrates previously unreported patterns of vegetation to reveal climate–vegetation relationships. The ability of the R packages ‘raster’ and ‘terra’ to process spatial data was enhanced through scripting to automate image analysis and mapping, and choosing Sudan for the case study enables us to present new perspectives for image processing.

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Empirical modelling of dust storm path attenuation for 5G mmWave

Mezaal,

Aripin,

Othman

et al. 2024

Results in Engineering

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Signal Attenuation Prediction Model for a 22 GHz Terrestrial Communication Link in Sudan Due to Dust and Sand Storms Using Machine Learning

Cited by 8 publications

References 15 publications

Earth and Martian Sand and Dust Storms: A Comprehensive Review of Attenuation Modelling and Measurements

Earth and Martian Sand and Dust Storms: A Comprehensive Review of Attenuation Modelling and Measurements

Multispectral Satellite Image Analysis for Computing Vegetation Indices by R in the Khartoum Region of Sudan, Northeast Africa

Empirical modelling of dust storm path attenuation for 5G mmWave

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