350 rub
Journal Radioengineering №6 for 2023 г.
Article in number:
Features of application of fractal Gaussian noise type signals in telecommunication systems
Type of article: scientific article
DOI: https://doi.org/10.18127/j00338486-202306-05
UDC: 621.391.8
Authors:

Ya.Ya. Levin1

1 SUAI (St. Petersburg, Russia)

Abstract:

Problem statement. At present, the properties of a separate type of pseudorandom signals such as fractal Gaussian noise remain insufficiently investigated. The existing discrete model of fractal Gaussian noise is characterized by the value of the Hurst exponent and the time scaling factor, the influence of which on the properties of fractal Gaussian noise is insufficiently investigated. The issue of synthesis of new types of fractal broadband signals of complex design, which can be used in noise-resistant telecommunication systems, is relevant.

Objective. Based on the mathematical model of fractal Gaussian noise, investigate the effect of the time scaling factor on the statistical, correlation and energy properties of fractal Gaussian noise signals.

Results. By the method of averaging over realizations the dependences of energy, correlation and statistical properties of signals of fractal Gaussian noise type, which can be used for coding information bits, on the time scaling factor were obtained.

Practical significance. According to the results of research on the properties of fractal Gaussian noise, the regularities of the passage of self-similar flows of Internet traffic in the approximation that they are self-similar and are described by a mathematical model of fractal Gaussian noise are established. When the intensity is increased up to requests/hour, the results of modeling the average transit time of traffic through the system for flows with different types of distribution show significant differences in the value of the average transit time of each request.

Pages: 41-49
For citation

Levin Ya.Ya. Features of application of fractal Gaussian noise type signals in telecommunication systems. Radiotekhnika. 2023. V. 87. № 6. P. 41−49. DOI: https://doi.org/10.18127/j00338486-202306-05 (In Russian)

References
  1. Potapov A.A. Opyt sozdanija i primery ispol'zovanija global'nogo fraktal'no-skejlingovogo metoda v radiofizike, radiolokacii i radiotehnike (1980–2015). Vestnik Chuvashskogo universiteta. 2015. № 1. S. 189-206 (in Russian).
  2. Oldham K.B., Spanier J. The Fractional Calculus. N.Y. Academic Press. 1974. 234 р.
  3. Bolotov V.N., Kolesnikov S.E., Tkach Yu.V., Khupchenko P. V. Fractal Communication System. Electromagnetic Phenomena. 2007. V. 7. № 1(18). Р. 174–179.
  4. Potapov A.A. The Textures, Fractal, Scaling Effects and Fractional Operators as a Basis of New Methods of Information Processing and Fractal Radio Systems Designing. Proc. SPIE. 2009. V. 7374. Р. 73740E-1–73740E-14.
  5. Mandelbrot B.B., Wallis J.R. Computer experiments with fractional Gaussian noises. Part 1. Averages and variances. Water Resours. Res. 1969. V. 5. P. 228–241.
  6. Mandelbrot B.B., Wallis J.R. Computer experiments with fractional Gaussian noises. Part 1. Averages and variances. Water Resours. Res. 1969. V. 5. P. 228–241.
  7. Mandelbrot B.B. Fractals: Form, Chance, and Dimension. San-Francisco. 1980.
  8. Feder E. Fraktaly. M.: Mir. 1991. 254 s. (in Russian).
  9. Lévy P. Processus stochastiques et mouvement Brownien. Suivi d’une note de M. Loève. Gauthier-Villars. Paris. 1948.
  10. Сергиенко А.Б. Цифровая обработка сигналов. СПб: Питер. 2002. 608 с.
  11. Li T.Y., Yorke J.A. Period three implies chaos. The American mathematical monthly. 1975. V. 82. № 10. P. 985–992.
  12. Karpov L.E. Arhitektura raspredelennyh sistem programmnogo obespechenija. M.: MAKS Press. 2007. 130 s. (in Russian).
  13. Bobalo Y., Politanskyi R., Klymash M. Traffic simulation in a telecommunication system based on queuing systems with different input flows. Econtechmod. An international quarterly journal on economics in technology, new technologies and modelling processes. 2015. V. 4. № 1. P. 11-15.
  14. Lihtcinder B.Ja. Interval'nyj metod analiza trafika mul'tiservisnyh setej. Prilozhenie k zhurnalu Infokommunikacionnye tehnologii. Modeli infokommunikacionnyh sistem: razrabotka i primenenie. 2013. Vyp. 8. S. 104-152 (in Russian).
  15. Kel'ton V., Lou A. Imitacionnoe modelirovanie. Klassika CS. Izd-e 3-e. SPb: Piter; Kiev: Izdatel'skaja gruppa BHV. 2004. 847 s. (in Russian).
  16. Dvornikov S.V., Krjachko A.F., Popov E.A., Dvornikov S.S., Tomashevich S.V. Kompensacija strukturnyh pomeh v radiochastotnyh kanalah upravlenija robototehnicheskih sistem. Radiotehnika. 2021. T. 85. № 11. S. 95-106. DOI: https://doi.org/10.18127/ j00338486-202111-15 (in Russian).
  17. Krjachko A.F., Jakushenko S.A., Dvornikov S.V., Popov E.A., Zabelo A.N. Metodika ocenki ustojchivosti seti mnogokanal'noj radiosvjazi na osnove reshenie zadachi Koshi dlja sistemy matrichnyh uravnenij Kolmogorova, opisyvajushhih ee sostojanie. Radiotehnika. 2020. T. 84. № 12(24). S. 112-120. DOI: 10.18127/j00338486-202012(24)-11 (in Russian).
  18. George E. P. Box, Mervyn E. Muller, "A note on the generation of random normal deviations", The Annals of Mathematical Statistics.Vol. 29, No. 2, 1958, pp. 610-611. DOI: 10.1214 / aoms / 1177706645, JSTOR : 2237361
Date of receipt: 15.05.2023
Approved after review: 19.05.2023
Accepted for publication: 26.05.2023