Model of a Self-Organizing Radio Network, Operating in a Complex Signal and Interference Environment.

Radio communication networks, including those that use adaptation, are designed for information exchange between individual correspondents and are usually built via radio routes, functioning ones in a complex signal and interference environment. It is necessary to take into account the degree of influence values adaptive parameters for indicators that describe accordance requirements communication requirements, the energy component of the radio link, as well as the amount of radio link resources spent on maintaining and restoring communication. Getting estimates of the boundaries of primary and secondary user traffic service characteristics in a self-organizing radio network, functioning in difficult signal-to-noise conditions it is relevant. The aim of the research is to increase the reliability of the simulation results by obtaining the boundary values of the throughput when transmitting information in a self-organizing radio communication network. Modeling of processes occurring in the radio communication network is carried out, and the following parameters are determined: boundary parameters of delay and loading; parameters of the output stream in a complex signal-interference environment. Conclusions about the advantages of the network calculus method based on the results of a series of calculations are presented. Analytical estimates of the quality of service provision in the radio communication system are obtained using the theory of network calculus. The developed mathematical model makes it possible to study the delay and load indicators in a self-organizing radio network during the information exchange of traffic of various types under the influence of intentional and unintentional interference. The results of analytical calculations obtained by applying the network calculus method can be used in the formation of control actions, as well as solving problems of increasing the stability of radio links.

1. Lipatnikov V.A., Parfirov V.A., Petrenko M.I. General model of self-organizing radio communication with stream multiplexing. Proceedings of the International Scientific and Practical Conference on Transport of Russia: Problems and Prospects ‒ 2022, 09‒10 November 2022, St. Petersburg, Russia, vol.1. St. Petersburg: IPT RAN Publ.; 2022. p.293‒297. (in Russ.)

2. Borisov V.I., Zinchuk V.M., Limarev A.E. Noise Immunity of Radio Communication Systems with Signal Spectrum Expansion by Carrier Pseudorandom Sequence Modulation. Moscow: Radio and Communications Publ.; 2003. 640 p. (in Russ.)

3. Rabin A.V. Noise immunity of digital communication systems with orthogonal coding and multi-position modulation. St. Petersburg: Saint Petersburg State University of Aerospace Instrumentation Publ.; 2019. 157 p. (in Russ.)

4. Glushankov E.I., Mityanin S.A. Analysis of the joint efficiency of spatial-time coding and spatial processing of signals in radio communication lines. Zametki uchenogo. 2022;6:187‒192. (in Russ.)

5. Dvornikov S.V., Dvornikov S. S., Manaenko S.S., Pshenichnikov A.V. Spectral-efficient signals with the continuous phase. Bulletin of Voronezh State Technical University. 2016;12(2):87‒93. (in Russ.)

6. Lipatnikov V.A., Sakharov D.V., Parfirov V.A., Petrenko M.I. Simulation model of a distributed radio monitoring object, reflecting the dynamics of movements and changing modes of operation of radio-electronic means. Proceedings of the Jubilee XVIII St. Petersburg International Conference on Regional Informatics (RI-2022), St. Petersburg, Russia, 26‒28 October 2022. St. Petersburg: Sankt-Peterburgskoe Obshchestvo informatiki vychislitelnoi tekhniki sistem sviazi i upravleniia Publ.; 2022. p.556‒558. (in Russ.)

7. Dvornikov S.V., Pshenichnikov A.V., Burykin D.A. Structural and functional model of a signal constellation with increased noise immunity. Information and Space. 2015;2:4‒7. (in Russ.)

8. Sorokin K. N. Model of a radio link parameter management system based on fuzzy logic. Information and Space. 2018;4: 39‒43. (in Russ.)

9. Fedorov I.V., Roslyakov A.V. Analysis of the characteristics of a cognitive radio network using network calculus. Proceedings of the XXIst International Scientific and Technical Conference “III Scientific Forum of Telecommunications: Theory and Technology”, TTT-2019, 18‒22 November 2019, Kazan, Russia, vol.1. Kazan: KAI Publ.; 2019. p.338‒339. (in Russ.)

10. Belov A., Lipatnikov V., Fedorov I. Model of a cognitive radio network based on the theory of stochastic network calculation. Proceedings of the Xth International Scientific and Technical and Scientific-Methodical Conference on Actual Problems of Infotelec Communications in Science and Education, 24‒25 February 2021, St. Petersburg, Russia, vol.1. St. Petersburg: The Bonch-Bruevich Saint Petersburg State University of Telecommunications Publ.; 2021. p.86‒90.p. (in Russ.)

11. Roslyakov A.V., Lysikov A.V., Vitevsky V.D. Network Calculus. Part 1. Theoretical Foundations. Infokommunikacionnye tehnologii. 2018;16(1):19‒33. (in Russ.) DOI:10.18469/ikt.2018.16.1.02

12. Kudryavtseva E.N., Roslyakov A.V. Basic principles and prospects of network calculus application. Infokommunikacionnye tehnologii. 2013;11(3):34‒39. (in Russ.)

13. Alekaev A.E., Belov A.V., Fedorov I.V. Method for multi-stage adaptation of low-energy radio line of short-wave range taking into account forecasting signal-interference situation. Proceedings of the International Scientific and Practical Conference on Transport of Russia: Problems and Prospects ‒ 2021, 09‒10 November 2021, St. Petersburg, Russia, vol.2. St. Petersburg: Solomenko Institute of Transport Problems of the Russian academy of sciences Publ.; 2021. p.157‒161. (in Russ.)

14. Krivulin N.K. Methods of idempotent algebra in problems of modeling and analysis of complex systems. St. Petersburg: The Bonch-Bruevich Saint Petersburg State University of Telecommunications Publ.; 2009. 256 p. (in Russ.)

15. Pshenichnikov A.V. Estimation of statistical parameters operating frequency of functional models of radio links in a conflict situation. Information and Space. 2018;1:46‒50. (in Russ.)