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Journal Nonlinear World №10 for 2014 г.
Article in number:
Polygaussian algorithm of signal processing in the presence of the non-gaussian interferences
Keywords:
signal processing
polygaussian models and methods
analyze of the noise immunity
computer simulation
Authors:
A.F. Nadeev - Dr.Sc. (Phys.-Math.), Professor, Kazan National Research Technical University named after A.N. Tupolev. E-mail: nad15@mail.ru
D.R. Rakhimov - Post-graduate Student, Engineer, Kazan National Research Technical University named after A.N. Tupolev. E-mail: Rakhimovdamir05@gmail.com
R.R. Zulkharneev - Post-graduate Student, Engineer, Kazan National Research Technical University named after A.N. Tupolev. E-mail: irtos@irz.ru
D.R. Rakhimov - Post-graduate Student, Engineer, Kazan National Research Technical University named after A.N. Tupolev. E-mail: Rakhimovdamir05@gmail.com
R.R. Zulkharneev - Post-graduate Student, Engineer, Kazan National Research Technical University named after A.N. Tupolev. E-mail: irtos@irz.ru
Abstract:
Actual direction of improving wireless communications system is to optimize the signal processing algorithms based on the use of adequate probabilistic models that take into account of the distribution of the interference.
Polygaussian models and methods ensures adequate representation of non-gaussian signals and interferences and provide solutions to the problem of synthesis of optimal signal processing algorithms. In this case, the task of analyzing the probability characteristics of these algorithms is a challenging and currently unsolved.
The purpose of this paper is to analyze the noise immunity of the signal processing algorithm in the presence of the non-gaussian interferences presented by the polygaussian model.
Optimal signal processing algorithm in the presence of the non-gaussian interferences presented by the polygaussian probabilistic model was synthesized in accordance with the Bayesian criterion.
Expressions are obtained for the probability characteristics of the signal processing algorithm in the presence of the non-gaussian interferences. For the validation of the obtained expressions software was developed. The analysis shows a high degree of compliance with the results of calculation and computer simulation.
It is shown that poligaussov algorithm in certain situations provides a significant gain in the error probability compared to the correlation algorithm in the presence of the non-gaussian interferences.
Pages: 92-95
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