Analysis of adequacy of mathematical models of parameters of partially coherent signals in radio-technical systems

The article discusses the analysis of the adequacy of Markov models of parameters of partially coherent signals in radio systems based on stochastic differential equations, carried out in the MATLAB software environment. The results of modeling one-dimensional non-Gaussian and Gaussian continuous, discrete-continuous and mixed random processes are presented. The method of functional (quasi-Gaussian) approximation represents the multidimensional probability distribution density through one-dimensional component densities and elements of the correlation matrix of a vector random process. For the multidimensional probability distribution densities obtained as a result of this representation and the multidimensional stochastic differential equations synthesized on their basis, the modeling of vector random processes describing the parameters of partially coherent signals in continuous communication channels is considered. The compliance of the obtained models with theoretical distributions is assessed using the Kolmogorov-Smirnov goodness-of-fit criterion. The ranges of changes in the parameters included in the SDE at which the model can be considered consistent, as well as the influence of the parameters on the shape of the distributions under consideration, are studied. Based on the results obtained, it is possible to estimate the ranges of changes in the parameters of the models that determine the form of stochastic differential equations, under which the requirements for the adequacy of the obtained models of partially coherent in the spatial and frequency sense of signals in radio systems are met.

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