Stochastic Approach to a Rain Attenuation Time Series Synthesizer for Heavy Rain Regions

In this work, a new rain attenuation time series synthesizer based on the stochastic approach is presented. The model combines a well-known interest-rate prediction model in finance namely the Cox-Ingersoll-Ross (CIR) model, and a stochastic differential equation approach to generate a long-term gamma distributed rain attenuation time series, particularly appropriate for heavy rain regions. The model parameters were derived from maximum-likelihood estimation (MLE) and Ordinary Least Square (OLS) methods. The predicted statistics from the CIR model with the OLS method are in good agreement with the measurement data collected in equatorial Malaysia while the MLE method overestimated the result. The proposed stochastic model could provide radio engineers an alternative solution for the design of propagation impairment mitigation techniques (PIMTs) to improve the Quality of Service (QoS) of wireless communication systems such as 5G propagation channel, in particular in heavy rain regions

An Analytical Prediction Model of Time Diversity Performance for Earth-Space Fade Mitigation

Time diversity (TD) has recently attracted attention as a promising and cost-efficient solution for high-frequency broadcast satellite applications. The present work proposes a general prediction model for the application of TD by approximating the time dynamics of rain attenuation through the use of the joint lognormal distribution. The proposed method is tested against experimental data and its performance is investigated with respect to the basic parameters of a satellite link

Survival probability of precipitations and rain attenuation in tropical and equatorial regions

This contribution presents a stochastic model useful for the generation of a long-term tropospheric rain attenuation time series for Earth space or a terrestrial radio link in tropical and equatorial heavy rain regions based on the well-known Cox-Ingersoll-Ross model previously employed in research in the fields of finance and economics. This model assumes typical gamma distribution for rain attenuation in heavy rain climatic regions and utilises the temporal dynamic of precipitation collected in equatorial Johor, Malaysia. Different formations of survival probability are also discussed. Furthermore, the correlation between these probabilities and the Markov process is determined, and information on the variance and autocorrelation function of rain events with respect to the particular characteristics of precipitation in this area is presented. The proposed technique proved to preserve the peculiarities of precipitation for an equatorial region and reproduce fairly good statistics of the rain attenuation correlation function that could help to improve the prediction of dynamic characteristics of rain fade events