MATHEMATICAL MODEL OF TRANSMISSION OF STOCHASTIC SIGNALS UNDER INTERFERENCE CONDITIONS
DOI:
https://doi.org/10.18372/2310-5461.70.21192Keywords:
stochastic signals, spectral efficiency, Karhunen–Loev transform, Voltaire series, information control systems, radio electronic interferenceAbstract
This article is devoted a mathematical model of stochastic signal transmission under conditions of radio-electronic interference based on the combined application of the Karhunen–Loev transform and adaptive Volterra series. The relevance of the study is due to modern requirements for combat control information systems, which in the conditions of large-scale armed aggression against Ukraine have become the main means of operational, tactical and strategic control of troops. Traditional linear signal processing methods do not provide the necessary compromise between spectral compactness, noise immunity and adaptability under conditions of non-stationary interference, multi-path fading and active radio-electronic interference, and also do not fully take into account the stochastic nature of signals, channel memory effects and nonlinear distortions arising under the influence of interference. To solve the problem, a combined application of the Karhunen–Loev transform for preliminary decorrelation and energy densification of stochastic signals with subsequent adaptive nonlinear processing using second-order Volterra series is proposed. The adaptability of the system is ensured by a multi-criteria optimization functional with dynamic adjustment of weight coefficients depending on the combat application scenario (stealth mode or active electronic warfare). The model describes the process of signal transmission through the channel, taking into account the impulse response of the environment and the generalized interference effect. The results of the study were obtained by simulation modeling in the Python 3.11 environment. A comparative analysis of the proposed approach with traditional signal processing methods (Fourier filtering, wavelet transform, Z-transform, classical Volterra model and separate application of the Karhunen–Loev transform) for different types of stochastic signals is carried out. The proposed approach provides increased spectral efficiency, noise immunity and adaptability of combat control information systems, which creates the prerequisites for its practical implementation in wireless combat control systems, secure communication facilities and sensor networks, where they are of particular importance.
References
Poisel R. A. Modern Communications Jamming Principles and Techniques. 2nd ed. Artech House, 2011. 870 p.
V. P. Ipatov, Spread Spectrum and CDMA: Principles and Applications, Chichester: John Wiley & Sons, 2005, https://doi.org/10.1002/0470091800
Papoulis A., Pillai S. U. Probability, Random Variables and Stochastic Processes. 4th ed. McGraw-Hill, 2002. 852 p.
Gariachiy M., Shcherbinin S. Improved method for generating stochastic signals using Volterra series. International Scientific-technical journal «Measuring and computing devices in technological processes». 2026. Issue 1. P. 47–60. https://doi.org/10.31891/2219-9365-2026-85-7
Gariachiy M., Shcherbinin S. Analysis of methods for enhancing spectral efficiency in information systems. Science-based Technology. 2025. № 3(67). P. 325–339. https://doi.org/10.18372/2310-5461.67.18510
Sklar B. Digital Communications: Fundamentals and Applications. 2nd ed. Prentice Hall, 2001. 1100 p.
Proakis J. G., Salehi M. Digital Communications. 5th ed. McGraw-Hill, 2008. 1152 p.
Haykin S. Communication Systems. 4th ed. Wiley, 2001.
Zhu L. et al. An Efficient Target Detection Algorithm via Karhunen–Loève Transform for FMCW Radar Applications // IET Signal Processing. 2022. Vol. 16. P. 800–810. https://doi.org/10.1049/sil2.12111.
Олецький О. В. Алгоритм відновлення одновимірних сигналів на основі інтегрального розкладу Карунена–Лоєва. Вісник НТУУ «КПІ». 2002. № 4. С. 74–79. https://ekmair.ukma.edu.ua/handle/123456789/9268.
Капустій Б. О., Русин Б. П., Таянов В. А. Критерії оптимізації набору спектральних складових перетворення Карунена–Лоєва при розрахунку диференціальної ймовірності правильного розпізнавання. Радіоелектроніка. 2004. № 3.
Закон України «Про електронні комунікації» від 16.12.2020 № 1089-IX (із змінами до 2024 року).
GaussianWaves. Volterra Series RF Power Amplifier Model. 2022. [Online]. Available: https://www.gaussianwaves.com (access data 14.03.2026)
Boyd S. et al. Analytical Foundations of Volterra Series. [Online]. Available: https://web.stanford.edu/~boyd/papers/pdf/analytical_volterra.pdf (access data 14.03.2026)
Araujo-Simon J. Compositional Nonlinear Audio Signal Processing with Volterra Series. arXiv:2308.07229v4, 2024. https://doi.org/10.48550/arXiv.2308.07229.
Chang H. et al. Research on the Karhunen–Loève Transform Method and Its Application to Hull Form Optimization. JMSE. 2023. Vol. 11, Iss. 230. https://doi.org/10.3390/jmse11010230
Simon M. K., Omura J. K., Scholtz R. A., Levitt B. K. Spread Spectrum Communications Handbook. McGraw-Hill, 1994.
Reed I. S., Chen X. Error-Control Coding for Data Networks. Springer, 1999. https://doi.org/10.1007/978-1-4615-5005-1.
Bracewell R. N. The Fourier Transform and Its Applications. McGraw-Hill, 2000.
Jain A. K. Fundamentals of Digital Image Processing. Prentice Hall, 1989.
Nature. Adaptive Stochastic Resonance for Unknown and Variable Input Signals. [Online].
https://doi.org/10.1038/s41598-017-02644-w
Перець, К., Лисечко, В., & Комар, О. (2025). Моделювання нелінійних компонентів сигналу на основі рядів Вольтерра у частотній області в процесі спектральної реконструкції. Комп’ютерно-інтегровані технології: освіта, наука, виробництво, (57), 192-201. https://doi.org/10.36910/6775-2524-0560-2024-57-23 .
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