Article or book title, author's surname, DOI

Determining Watterson model time delays using adaptive filters

A.S. Kirillov1

research article UDC 621.396.96 Pages: 5-13 doi.org/10.18127/j00338486-202410-01

  1. 1 PJSC “Radiofizika” (Moscow, Russia); Moscow Institute of Physics and Technology (National Research University) (Dolgoprudny, Russia)

Abstract

Short radio waves have the property of being reflected from the ionosphere, which is why data transmission via HF communication channels can be carried out over many kilometers without additional transmitting devices. The use of broadband communication channels increases the data transmission speed, but at the same time leads to severe distortion of the received signal. Using the Watterson model, the HF communication channel was simulated in Matlab in the Simulink environment. For various possible values of the model parameters, least mean squares (LMS) equalizer algorithms were used to determine these coefficients.

Received
02.09.2024
Approved after review
24.09.2024
Accepted
30.09.2024

How to cite

Кириллов А.С. Определение параметров модели Ваттерсона с помощью адаптивных фильтров // Радиотехника. 2024. Т. 88. № 10. С. 5-13. DOI: https://doi.org/10.18127/j00338486-202410-01

References
  1. Watterson C.C., Juroshek J.R. and Bensema W.D. Experimental confirmation of an HF channel model. IEEE(R) Trans. commun. Technol. 1970. V. COM-18. № Dec. 6.
  2. Recommendation ITU-R F.1487, Testing of HF modems with bandwidths of up to about 12 kHz using ionospheric channel simulators. 2000. 
  3. Recommendation ITU-R F.520, Use of high frequency ionospheric channel simulators. 1992.
  4. Kirillov A.S. Machine learning algorithms for reception of a signal of digital radio lines. XV All-Russian Conference «Radiolocation and Radio Communication». Collection of works. Moscow. IRE im. V.A. Kotelnikov RAS. 2022.
  5. Kirillov A.S. Machine Learning Algorithms for Signal Demodulation and Determination of HF Communication Channel Parameters. IEEE Radiation and Scattering of Electromagnetic Waves (RSEMW). 2023. P. 268-271. DOI: 10.1109/RSEMW58451.2023.