Time diversity analysis based on predicted rain attenuation at KU, KA and V- bands using synthetic storm technique
Satellite communication in the future is shifting to higher frequency Ka and V-bands. The fundamental issue in designing viable earth-to-satellite communication links at these bands is rain fade. In tropical areas, the problem is increased severely by the fact that high-intensity r...
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| Main Authors: | , , , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English English |
| Published: |
IEEE
2021
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/90604/1/09467239.pdf http://irep.iium.edu.my/90604/7/90604_Time%20Diversity%20Analysis%20Based%20on%20Predicted_schedule.pdf http://irep.iium.edu.my/90604/ https://ieeexplore-ieee-org.ezlib.iium.edu.my/document/9467239 |
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| Summary: | Satellite communication in the future is shifting to higher frequency Ka and
V-bands. The fundamental issue in designing viable earth-to-satellite communication links at these
bands is rain fade. In tropical areas, the problem is increased severely by the fact that
high-intensity rainfall occurs for the majority of times in the year. One of the
potential solutions presented by researchers to combat attenuation due to rain is the time
diversity method. To explore the improvement, measured real-time rain attenuation
data are necessary for time diversity analysis. However, the problem is that data in
higher frequency bands such as the Ka and V bands are not available in most of the
places. As a result, the Synthetic Storm Technique (SST) can be used to convert real-time
rain rate data into real-time rain attenuation data at any required frequency. This
research analyses data collected at IIUM's Kuala Lumpur campus over one-year period using
one-minute integration time. Synthetic Storm Technique (SST) is used to estimate rain
attenuation for Ku, Ka, and V-bands based on one-year recorded rain rate data. Time
diversity gains are assessed and compared to available measured gain at Ku-band and that
predicted by Matricciani's model using anticipated rain attenuation time series. |
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