A modified rain attenuation prediction model for tropical V‐band satellite earth link

Badron, Khairayu; Ismail, Ahmad Fadzil; Islam, Md. Rafiqul; Abdullah, Khaizuran; Din, Jafri; Tharek, A.R.

doi:10.1002/sat.1071

Cited by 8 publications

(4 citation statements)

References 22 publications

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“…Sharan presented work regarding the prediction of rainfall based on an average of three methods where the historical rain data of Bihar were selected for projection and found that the predicted results were quite close to the actual rainfall data for 2013 [23]. Many other researchers have shown that rain is predictable and this information can be used in many applications [24,25].…”

Section: Related Workmentioning

confidence: 99%

Notice of Retraction: Short-term and local rainfall probability prediction based on a dislocation support vector machine model using satellite and in-situ observational data

Chen

et al. 2024

IEEE Access

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Short-term and local rainfall commonly occurs in southern China, and can result in intensive precipitation in the local region over a very short time. Considerable precipitation could cause an intense flood within a city when the runoff exceeds the capacity of a city drainage system. Predicting rainfall probability accurately is among the important scientific problems in meteorology and remains a challenge. In this study, a dislocation machine learning method based on a support vector machine was used to predict short-term and local rainfall probability using Feng Yun II geostationary meteorological satellite imagery and ground in situ observational data. The results were validated by a traditional threat score, which is commonly used in evaluation of weather predictions. The results indicate that the proposed algorithm can achieve good performance for a 1-h to 6-h forecast. The result implies that prediction accuracy could be improved by using a machine

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Section: Related Workmentioning

confidence: 99%

Notice of Retraction: Short-term and local rainfall probability prediction based on a dislocation support vector machine model using satellite and in-situ observational data

Chen

et al. 2024

IEEE Access

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“…To transform the rainfall rate into rain attenuation , ITU‐R recommendation P.618‐12 is followed using a frequency of 22 GHz (the highest frequency in the 21.4–22 GHz band which is allocated next satellite broadcasting in ITU region 1 and 3). The rainfall rate exceeded at 0.01% of the time is used for predicting the rain attenuation value.…”

Section: Simulation Resultsmentioning

confidence: 99%

Prediction model of time diversity using Japan rain radar data

Chodkaveekityada

Fukuchi

2016

Satell Commun Network

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Summary The effects of rain attenuation on communication systems will become more pronounced in future satellite communication systems, especially with the planned use of the 21‐GHz band or higher‐frequency bands. Diversity techniques provide a solution to mitigate rain attenuation effects. This study proposes a time diversity technique, one such technique that is likely to demonstrate high effectiveness. To model the system, rainfall rate statistics are necessary, and reliability is improved as the amount of statistical data increases. This paper derives the cumulative distribution of the rainfall rate across Japan over 4 years using rain radar data from the automated meteorological data acquisition system and ground‐based rain radar network and evaluates the rainfall rate at 23 observation points across Japan. We carry out a performance evaluation for all locations within Japan to confirm the efficiency of the time diversity method. Finally, we propose prediction model of the time diversity gain for Japan and other significant parameter which is time correlation of rainfall rate that was found from the time diversity results for further investigation. Copyright © 2016 John Wiley & Sons, Ltd.

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“…The proper scaling mechanism regarding these parameters is yet to be devised. The ITU-R model is the most significant model that has been moderated for tropical regions by many researchers [29,[142][143][144][145][146]. However, these models do not support the scaling properties.…”

Section: Scaling Improvementmentioning

confidence: 99%

A Survey of Rain Fade Models for Earth–Space Telecommunication Links—Taxonomy, Methods, and Comparative Study

2021

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Satellite communication is a promising transmission technique to implement 5G and beyond networks. Attenuation due to rain begins at a frequency of 10 GHz in temperate regions. However, some research indicates that such attenuation effects start from 5–7 GHz, especially in tropical regions. Therefore, modeling rain attenuation is significant for propagating electromagnetic waves to achieve the required quality of service. In this survey, different slant link rain attenuation prediction models have been examined, classified, and analyzed, and various features like improvements, drawbacks, and particular aspects of these models have been tabulated. This survey provides various techniques for obtaining input data sets, including rain height, efficient trajectory length measurement techniques, and rainfall rate conversion procedures. No survey of the Earth–space link models for rain attenuation is available to the best of our knowledge. In this study, 23 rain attenuation models have been investigated. For easy readability and conciseness, the details of each model have not been included. The comparative analysis will assist in propagation modeling and planning the link budget of slant links.

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A modified rain attenuation prediction model for tropical V‐band satellite earth link

Cited by 8 publications

References 22 publications

Notice of Retraction: Short-term and local rainfall probability prediction based on a dislocation support vector machine model using satellite and in-situ observational data

Notice of Retraction: Short-term and local rainfall probability prediction based on a dislocation support vector machine model using satellite and in-situ observational data

Prediction model of time diversity using Japan rain radar data

A Survey of Rain Fade Models for Earth–Space Telecommunication Links—Taxonomy, Methods, and Comparative Study

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