Precipitation type detection and their impacts on microwave radio connections

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Supervisor:
Dr. Csurgai-Horváth László
Department of Broadband Infocommunications and Electromagnetic Theory

Environmental effects have high impact on point-to-point ground microwave radio links. Among these effects the attenuation of several types of precipitations in the atmosphere should be emphasized, which is the primary subject of my thesis. Their influence already appear in the frequency range of some GHz’s and the higher the frequency the higher the impact is. The most often studied factor is rain and attenuation due to rain is easy to model with the help of specific ITU-R standards. Precipitations can be detected, measured by several meteorological instruments. An analysis like that can be made with the PWD11 present weather detector that is capable of simultaneously measuring several type of weather conditions. The measurement system operating at the department measures microwave link’s signal power along with weather data. Sensor measurements and signal power data can be processed with the Matlab program that allows transforming input into a modelling-ready form. Having done so it is possible to detect the effects of various kinds of moisture or even fading phenomenon from the received signal power. It is an interesting fact that a countrywide average rain intensity value (R0.01=42 mm/h) is used in calculations in entire Hungary though measurements vary with different regions. It will be revealed that this region-specific value is calculable without measurements thanks to ITU models which can make future models more accurate Nevertheless calculations are not limited to the recommended 30 GHz range but it is applicable for higher frequencies - as my studies revealed it. Other interesting factor to analyse is formation of fading events since these can have a significant effect on signal transmission. This makes it important to recognize change of environmental parameters as soon as possible. In my thesis I worked with the detection and identification of precipitation types from the signal power data, where calculating fade slope helped deduce the type of moisture. Moisture type results can be verified with PWD11’s built-in moisture type detector.

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