Development of an empirical dust storm attenuation prediction model for microwave links in arid area – a proposed framework
Wireless communication service providers are currently facing challenges due to the congested frequencies spectrum which has imposed the use of higher and higher frequencies. However, higher frequency bands are more sensitive to weather condition and the microwave signal attenuation due to atmospher...
| Main Authors: | , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English English English English English |
| Published: |
IEEE
2014
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/39167/ http://irep.iium.edu.my/39167/1/ICCCE2014_Paper_ID1109.pdf http://irep.iium.edu.my/39167/4/Sessions.pdf http://irep.iium.edu.my/39167/5/Main.pdf http://irep.iium.edu.my/39167/10/39167_development_of_an_empirical_dust_storm.pdf http://irep.iium.edu.my/39167/13/39167_Development%20of%20an%20empirical%20dust%20storm%20attenuation_Scopus.pdf |
| Summary: | Wireless communication service providers are currently facing challenges due to the congested frequencies spectrum which has imposed the use of higher and higher frequencies. However, higher frequency bands are more sensitive to weather condition and the microwave signal attenuation due to atmospheric particles increases rapidly at higher frequency bands. Consequently dust storms and other phenomena cause signal attenuation which can limit the performance of wireless communication systems for the frequencies above 10GHz in arid area. The paper aim is to show that real dust storm is a complex phenomena which is difficult to be described by the theoretical physical or mathematical models. An empirical dust storm prediction model based on the long term statistical observations of dust storm properties and its corresponding microwave signal levels will be a step forward to provide microwave link designers with a precise tool to rely on. This paper has proposed a research framework to collect necessary data from Khartoum, Sudan and develop an empirical attenuation prediction model. |
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