Site diversity is an effective rain attenuation mitigation technique, especially in the tropical region with high rainfall rate. The impact of different factors such as site separation distance, frequency, elevation angle, polarization angle, baseline orientation and wind direction is assessed. Results are compared to those reported in existing literature and also compared to the commonly used ITU-R site diversity prediction models. The effect of the wind direction on site diversity is also presented. It can be observed that diversity gain is highly dependent on the site separation distance, elevation angle and wind direction but independent of the frequency, baseline angle and polarization angle of the signal. This study is useful for the implementation of site diversity as a rain attenuation mitigation technique.
This paper proposes a model for predicting rain attenuation in the tropical region. Slant path rain attenuation measurements were carried out in Singapore by analyzing the beacon signals from two satellites, namely WINDS and GE23, operating at frequencies of 18.9 and 12.75 GHz respectively. Rainfall rates at the location of the beacon receivers were recorded. The cumulative distributions of the rainfall rate and the corresponding rain attenuation are presented and analyzed. It is found that the cumulative distribution of the measured rainfall rate is close to that predicted by the ITU-R model. Measurement data from a total of nine countries are compared with four existing rain attenuation prediction models, namely the Yamada, DAH, Karasawa and Ramachandran models. Results show that although three of these models have relatively good prediction capability for the tropical region, they could be improved. Therefore, in this paper, a slant path rain attenuation model suitable for the tropical region is proposed. This is done by using the complementary cumulative distributions of rain attenuation for satellite links measured in Singapore and five other tropical countries. The proposed model is found to outperform existing models.
Abstract-A Z-R relation is derived using a data set which consists of nine rain events selected from Singapore's drop size distribution. Rain events are separated into convective and stratiform types of rain using two methods: the Gamache-Houze method, a simple threshold technique, and the Atlas-Ulbrich method. In the Atlas-Ulbrich method, the variability of the rain integral parameters R, Z, N w , D 0 and gamma model parameter µ are used for the classification of rain into convective, stratiform and transition. Z-R relations are derived for each type of rain after classification. The changes in the coefficients of the Z-R relations for different rain events are plotted and analyzed. The Z-R relations of the different methods using the Singapore data are compared and analyzed. It is concluded that the coefficient A of the Z-R relation is higher for the convective stage followed by the stratiform and transition stages. The coefficient b values are higher for the transition stage followed by the stratiform and convective stages. Reflectivities are extracted from RADAR data above NTU site for rain events and compared with the reflectivities derived from the distrometer data. Rain rates retrieved from RADAR data using the proposed relations from Singapore's data set are compared with the distrometer rain rates. The RADAR extracted rain rates are found to be constantly lower than the distrometer derived rain rates but matches well.
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