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International Journal of Electrical and Computer Engineering, Volume 6, Issue 5, 2016, pp. 2379-2386

Stochastic approach to a rain attenuation time seris synthesizer for heavy rain regions

Abstract :

In this work, a new rain attenuation time series synthesizer based on the stochastic approach is presented. The model combines a well-known interestrate prediction model in finance namely the Cox-Ingersoll-Ross (CIR) model, and a stochastic differential equation approach to generate a longterm gamma distributed rain attenuation time series, particularly appropriate for heavy rain regions. The model parameters were derived from maximumlikelihood 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. Copyright © 2016 Institute of Advanced Engineering and Science. All rights reserved.

Keywords : Heavy rain regions,Radiowave propagation,Rain attenuation,Stochastic approach,Time series synthesizer
Subject Area : Computer Science(all) Electrical and Electronic Engineering Computer Networks and Communications Hardware and Architecture

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