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| Titel |
Short-term prediction of rain attenuation level and volatility in Earth-to-Satellite links at EHF band |
| VerfasserIn |
L. Montera, C. Mallet, L. Barthes, P. Golé |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1023-5809
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| Digitales Dokument |
URL |
| Erschienen |
In: Nonlinear Processes in Geophysics ; 15, no. 4 ; Nr. 15, no. 4 (2008-08-01), S.631-643 |
| Datensatznummer |
250012716
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| Publikation (Nr.) |
 copernicus.org/npg-15-631-2008.pdf |
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| Zusammenfassung |
This paper shows how nonlinear models originally developed in the finance
field can be used to predict rain attenuation level and volatility in
Earth-to-Satellite links operating at the Extremely High Frequencies band
(EHF, 20–50 GHz). A common approach to solving this problem is to consider
that the prediction error corresponds only to scintillations, whose variance
is assumed to be constant. Nevertheless, this assumption does not seem to be
realistic because of the heteroscedasticity of error time series: the
variance of the prediction error is found to be time-varying and has to be
modeled. Since rain attenuation time series behave similarly to certain
stocks or foreign exchange rates, a switching ARIMA/GARCH model was
implemented. The originality of this model is that not only the attenuation
level, but also the error conditional distribution are predicted. It allows
an accurate upper-bound of the future attenuation to be estimated in real
time that minimizes the cost of Fade Mitigation Techniques (FMT) and
therefore enables the communication system to reach a high percentage of
availability. The performance of the switching ARIMA/GARCH model was
estimated using a measurement database of the Olympus satellite 20/30 GHz
beacons and this model is shown to outperform significantly other existing
models.
The model also includes frequency scaling from the downlink frequency to the
uplink frequency. The attenuation effects (gases, clouds and rain) are first
separated with a neural network and then scaled using specific scaling
factors. As to the resulting uplink prediction error, the error contribution
of the frequency scaling step is shown to be larger than that of the
downlink prediction, indicating that further study should focus on improving
the accuracy of the scaling factor. |
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