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Prediction of annual joint rain fade on EHF networks by weighted rain field selection

Paulson, K. S.; Chinda, I. D.

Authors

I. D. Chinda

Abstract

©2015. American Geophysical Union. All Rights Reserved. We present a computationally efficient method to predict joint rain fade on arbitrary networks of microwave links. Methods based on synthetic rain fields composed of a superposition of rain cells have been shown to produce useful predictions of joint fade, with low computational overhead. Other methods using rain fields derived from radar systems have much higher computational overhead but provide better predictions. The proposed method combines the best features of both methods by using a small number of measured rain fields to produce annual fade predictions. Rain fields are grouped into heavy rain and light rain groups by maximum rain rate. A small selection of rain fields from each group are downscaled and fade predictions generated by pseudointegration of specific attenuation. This paper presents a method to optimize the weights used to combine the heavy rain and light rain fade predictions to yield an estimate of the average annual distribution. The algorithm presented yields estimates of average annual fade distributions with an error small compared to year-to-year variation, using only 0.2% of the annual data set of rain fields.

Journal Article Type Article
Publication Date Aug 31, 2015
Journal Radio science
Print ISSN 0048-6604
Electronic ISSN 1944-799X
Publisher American Geophysical Union
Peer Reviewed Peer Reviewed
Volume 50
Issue 8
Pages 827-836
Institution Citation Paulson, K. S., & Chinda, I. D. (2015). Prediction of annual joint rain fade on EHF networks by weighted rain field selection. Radio science, 50(8), 827-836. https://doi.org/10.1002/2015RS005695
DOI https://doi.org/10.1002/2015RS005695
Keywords Rain fade, Network fade, Joint fade, Estimation
Publisher URL http://onlinelibrary.wiley.com/doi/10.1002/2015RS005695/full
Additional Information Copy of article which has been published in: Radio science, 2015, v.50, issue 8.

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Copyright Statement
©2015. American Geophysical Union. All Rights Reserved.



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