Development of methodological principles of routing in networks of special communication in conditions of fire storm and radio-electronic suppression

Keywords: artificial intelligence, electronic environment, intelligent systems, decision making support systems


Decision making support systems are actively used in the processing of large data sets, process forecasting, providing information support to the decision-making process by decision-makers. However, there are problems with the transmission of information: the transmission of information takes place in a complex electronic environment against the background of interference; radio communication systems are the objects of primary fire damage due to high radio visibility. This article develops the methodological principles of routing in special communication networks in the conditions of fire damage and electronic suppression. The purpose of this research is to increase the efficiency of information transfer under the influence of destabilizing factors. The proposed methodological principles are based on the theory of artificial intelligence. The research presents a mathematical formulation of the problem of routing in special-purpose radio networks and developed a method of routing in special-purpose radio networks.

The efficiency of information processing is achieved through training in the architecture of artificial neural networks; taking into account the type of uncertainty of the information to be assessed; use of the ant algorithm. The approbation of the use of the offered technique on the example of the estimation of information transfer in the conditions of influence of destabilizing factors is carried out. The proposed methodological principles should be used in the development of software for programmable devices of communication and in the modernization of existing and development of new radio communication devices. This example showed an increase in the efficiency of information transmission in radio communication systems at the level of 15–25 % on the criterion of efficiency


Download data is not yet available.

Author Biographies

Oleg Sova, Military institute of Telecommunications and Informatization named after Heroes of Kruty

Department of Automated Control Systems

Yurii Zhuravskyi, Zhytomyr Military Institute named after S. P. Koroliov

Department of Electrical Engineering and Electronics

Yuliia Vakulenko, Poltava State Agrarian University

Department of Information Systems and Technologies

Andrii Shyshatskyi, Central Scientifically-Research Institute of Arming and Military Equipment of the Armed Forces of Ukraine

Research Department of Electronic Warfare Development

Olha Salnikova, National Defence University of Ukraine named after Ivan Cherniakhovskyi

Educational and Research Center of Strategic Communications in the Sphere of National Security and Defence

Oleksii Nalapko, Central Scientifically-Research Institute of Arming and Military Equipment of the Armed Forces of Ukraine

Research Laboratory of Automation of Scientific Researches


Kuchuk, N., Mohammed, A. S., Shyshatskyi, A., Nalapko, O. (2019). The method of improving the efficiency of routes selection in networks of connection with the possibility of self-organization. International Journal of Advanced Trends in Computer Science and Engineering, 8 (1.2). Available at:

Sova, O., Turinskyi, O., Shyshatskyi, A., Dudnyk, V., Zhyvotovskyi, R., Prokopenko, Y. et. al. (2020). Development of an algorithm to train artificial neural networks for intelligent decision support systems. Eastern-European Journal of Enterprise Technologies, 1 (9 (103)), 46–55. doi:

Makarenko, S. I., Mikhailov, R. L. (2013). Otsenka ustoychivosti seti svyazi v usloviyah vozdeystviya na nee destabihziruyushhih faktorov. Radioengineering and Telecommunication Systems, 4, 69–79.

Bodyanskiy, E., Strukov, V., Uzlov, D. (2017). Generalized metrics in the problem of analysis of multidimensional data with different scales. Zbirnyk naukovykh prats’ Kharkivs’koho natsional’noho universytetu Povitryanykh Syl, 3 (52), 98–101.

Semenov, V. V., Lebedev, I. S. (2019). Processing of signal information in problems of monitoring information security of unmanned autonomous objects. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 19 (3), 492–498. doi:

Zhou, S., Yin, Z., Wu, Z., Chen, Y., Zhao, N., Yang, Z. (2019). A robust modulation classification method using convolutional neural networks. EURASIP Journal on Advances in Signal Processing, 2019 (1). doi:

Shaheen, E. M., Samir, M. (2013). Jamming Impact on the Performance of MIMO Space Time Block Coding Systems over Multi-path Fading Channel. REV Journal on Electronics and Communications, 3 (1-2). doi:

Malik, S., Kumar, S. (2017). Optimized Phase Noise Compensation Technique using Neural Network. Indian Journal of Science and Technology, 10 (5), 1–6. doi:

Rotshteyn, A. P (1999). Intellektual'niye tekhnologii identifikatsii: nechotkiye mnozhestva, geneticheskiye algoritmy, neyronniye seti. Vinnitsa: “UNIVERSUM”, 320.

Mazhara, O. A. (2015). Treat algorithm implementation by the basic match algorithm based on clips programming environment. Elektronnoye modelirovaniye, 37 (5), 61‒75.

Bolotova, S. Yu., Makhortov, S. D. (2011). Algoritmy relevantnogo obratnogo vyvoda na osnove resheniya produktsionno-logicheskikh uravneniy. Iskusstvenniy intellekt prinyatiye resheniyi, 2, 40‒50.

Zhyvotovskyi, R., Shyshatskyi, A., Petruk, S. (2017). Structural-semantic model of communication channel. 2017 4th International Scientific-Practical Conference Problems of Infocommunications. Science and Technology (PIC S&T). doi:

👁 33
⬇ 32
How to Cite
Sova, O., Zhuravskyi, Y., Vakulenko, Y., Shyshatskyi, A., Salnikova, O., & Nalapko, O. (2022). Development of methodological principles of routing in networks of special communication in conditions of fire storm and radio-electronic suppression. EUREKA: Physics and Engineering, (3), 159-166.
Computer Science