Pareto-Rayleigh (PR) distribution (a member of Pareto-X family proposed in [1]) is considered here to study. The estimated values the model parameters are derived by maximum likelihood estimation process. Different important properties introduced obtained. Four real-life applications studied from various fields evaluate applicability PR model. An exclusive simulation has been conducted observe ...

One of the applications with nonlinear nonstationary signals lies in mobile communications where nonlinear information bearing signals are faded by the time-varying propagation medium. Consequently, the envelope of the received signal is often modelled by a Rayleigh distribution. This Rayleigh fading severely degrades the performance of the mobile radio transmission system. Diversity reception ...

Efficient simulation models for correlated Nakagami-m fading channels are required for the development, performance evaluation and validation of diversity combining systems in general fading channels. We propose a theoretical explanation of the Nakagami-m distribution, as a natural extension of the Rayleigh fading model. In this model, a Nakagami random variable is viewed as the norm of an mdim...

We study the fine-scale statistics of temperature and its derivatives in turbulent RayleighBénard convection. Direct numerical simulations are carried out in a cylindrical cell with unit aspect ratio filled with a fluid with Prandtl number equal to 0.7 for Rayleigh numbers between 10 and 10. The probability density function of the temperature or its fluctuations is found to be always non-Gaussi...

This paper presents algorithms for generating random variables for exponential/Rayleigh/ Weibull, Nakagami-m and Rician copulas with any desired copula parameter(s), using the direct conditional cumulative distribution function method and the complex Gaussian distribution method. Moreover, a novel method for optimal copula selection is also proposed, based on the criterion that for a given seri...

In a multipath fading channel, the transmitted signal travels through several different paths to the receiver. In each path, amplitude and phase of the signal vary in a random manner. It is common to consider the number of paths as a large constant and to model random fluctuations of the phase by the uniform probability density function (PDF). However, these assumptions are not realistic in man...