Analysis of Using of Fractal Signals for Noise Immune Information Transmission Systems

Veryga, Andrij; Politanskyi, Ruslan; Lesinskyi, Valentyn; Руда, Тетяна

doi:10.1109/tcset49122.2020.235414

Cited by 11 publications

(3 citation statements)

References 1 publication

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“…Traditionally, the most developed and widespread of them are the tensor method of network modeling [1,2], methods based on the Kerners theory of three phases [3], as well as numerous modifications of random graphs theory (Erdos-Reney, Watts-Strogats, Barabashi-Alberta models), percolation theory [4]. This is important for ensuring the security of information systems using telecommunication technologies [5,6], as well as other aspects of protected data transfer [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Entropy calculation for networks with determined values of flows in nodes

Politanskyi¹,

Bobalo²,

Zarytska³

et al. 2022

Math. Model. Comput.

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The paper analyses a network with given input and output flows in each of its nodes. The basis of this analysis is the algorithm for determining the set of solutions of the linear equations system, using the Gaussian method. The power of the set determines the structural entropy of the system. By introducing uncertainty into the value of part of the information flows, the deviation of the network from its equilibrium state is simulated. The set of potential solutions, as a part of the total set of the system solutions, determines the statistical entropy of the system. The probability entropy is calculated for a network with four nodes and a total flow of 10 erlangs with a sampling step of 1 erlang. Calculated entropy values for 1, 2, 3, and 4 uncertain flows out of a total of 16 flows that are transmitted between nodes of the fully connected network. As a result of the conducted statistical analysis of entropy values, the optimal number of statistical intervals for entropy values is determined: 4, 11, 24, and 43 intervals for 1, 2, 3, and 4 uncertain flows, respectively. This makes it possible to highlight the set of flows in the system that have the greatest influence on the entropy value in the system. The obtained results are of practical importance, as they enable the detection of deviations of the network from its equilibrium state by monitoring the passage of traffic on individual branches of a complex telecommunication network. Since, as shown in our previous works, the task of determining the complete set of solutions of the system for the number of nodes greater than 4 has a significant computational complexity, the application of the algorithm to such networks requires an increase in the discretization step of the values of information flows in the network. Another way to reduce computational complexity can be to reduce the set of analysed solutions to a subset of solutions close to the equilibrium state of the system.

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Section: Introductionmentioning

confidence: 99%

Entropy calculation for networks with determined values of flows in nodes

Politanskyi¹,

Bobalo²,

Zarytska³

et al. 2022

Math. Model. Comput.

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show abstract

“…That's why it is necessary to study the information transfer methods aimed at improving energy efficiency (i.e. reducing energy costs), including artificial intelligence [1] for frequency allocation, blockchain technology for infrastructure sharing, and the search for new signal generation methods and their modulation [2][3][4][5] to overcome intersymbol and interchannel interference. All this leads to a global trend in the development of telecommunications technologies in the direction of their convergence [6].…”

Section: Introductionmentioning

confidence: 99%

Research of distribution of information flows in a network

Politanskyi¹,

Zarytska²,

Vistak³

et al. 2021

Math. Model. Comput.

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The algorithm for determining information flows in the network is developed and studied, taking into account restrictions on the input and output flows values in each node of the system. The algorithm is based on the Gaussian method of solving linear equations systems in case when the rank of the equivalent system matrix, is less than the number of unknown variables in the system. Using this algorithm, the capacities of sets of the integer solutions for networks with 2 nodes (flow intensity up to 200), 3 nodes (flow intensity up to 20) and 4 nodes (flow intensity up to 10) are calculated.

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“…The development of telecommunication technologies has led to an active search for new information transmission technologies which use complex chaotic signals [1], methods of signal processing [2] and modulation using artificial intelligence systems [3]. The transition to new frequency bands and the complexity of signal processing processes led to the search for new models and methods in radio systems [4,5].…”

Section: Introductionmentioning

confidence: 99%

Simulation of the Propagation of Electromagnetic Oscillations by the Method of the Modified Equation of the Telegraph Line

Politansky

Nytrebych

Petryshyn

et al. 2021

Phys. Chem. Solid St.

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The article considers the physical processes associated with the propagation of electromagnetic oscillations in a long line, the size of which is the same or slightly greater than the length of the electromagnetic wave (not more than ten times). As a research method, the differential-symbolic method is used, which is applied to the modified equation of the telegraph line. The boundary conditions for the two-point problem as well as additional parameters that are coefficients for the first derivatives in terms of coordinate and time in comparison with the classical equation of the telegraph line are considered as parameters for controlling the process of propagation of electromagnetic oscillations. Based on the differential-symbolic method, the boundary conditions of the two-point problem are found, under which the most characteristic oscillatory processes are realized in a long line. Based on the research, it is possible to draw conclusions about the effectiveness of analytical methods for the analysis of specific technical objects and control of the processes that take place in them.

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Analysis of Using of Fractal Signals for Noise Immune Information Transmission Systems

Cited by 11 publications

References 1 publication

Entropy calculation for networks with determined values of flows in nodes

Entropy calculation for networks with determined values of flows in nodes

Research of distribution of information flows in a network

Simulation of the Propagation of Electromagnetic Oscillations by the Method of the Modified Equation of the Telegraph Line

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