Selected Topics in Transplant Hepatology

Keisham, Amarjit; Roy, Akash; Singh, Virendra

doi:10.1007/978-981-16-8448-7_19

Cited by 1 publication

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“…2012 [183] To develop an ANN method based on the extinction cross-section data for rain attenuation prediction in microwave and millimeter wave frequencies.…”

Section: Root Mean Squared Error (Rsme) and Correlationmentioning

confidence: 99%

A Review on Rain Signal Attenuation Modeling, Analysis and Validation Techniques: Advances, Challenges and Future Direction

et al. 2022

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Radio waves are attenuated by atmospheric phenomena such as snow, rain, dust, clouds, and ice, which absorb radio signals. Signal attenuation becomes more severe at extremely high frequencies, usually above 10 GHz. In typical equatorial and tropical locations, rain attenuation is more prevalent. Some established research works have attempted to provide state-of-the-art reviews on modeling and analysis of rain attenuation in the context of extremely high frequencies. However, the existing review works conducted over three decades (1990 to 2022), have not adequately provided comprehensive taxonomies for each method of rain attenuation modeling to expose the trends and possible future research directions. Also, taxonomies of the methods of model validation and regional developmental efforts on rain attenuation modeling have not been explicitly highlighted in the literature. To address these gaps, this paper conducted an extensive literature survey on rain attenuation modeling, methods of analyses, and model validation techniques, leveraging the ITU-R regional categorizations. Specifically, taxonomies in different rain attenuation modeling and analysis areas are extensively discussed. Key findings from the detailed survey have shown that many open research questions, challenges, and applications could open up new research frontiers, leading to novel findings in rain attenuation. Finally, this study is expected to be reference material for the design and analysis of rain attenuation.

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“…2012 [183] To develop an ANN method based on the extinction cross-section data for rain attenuation prediction in microwave and millimeter wave frequencies.…”

Section: Root Mean Squared Error (Rsme) and Correlationmentioning

confidence: 99%