A.P. Pavlov1, I.E. Kashchenko2, A.V. Bakhmutskaya3

1-3 Omsk Scientific Center SB RAS (Institute of Radiophysics and Physical Electronics) (Omsk, Russia)

Currently, one of the key factors determining the energy efficiency of a radio transmitting system is the degree of matching between the radio transmitting device and the antenna. For this reason, HF radio transmission systems often include automatic antenna matching devices that give the best degree of matching over the entire frequency band. However, these devices, due to the slow convergence of algorithms based on classical search methods used to determine the optimal state of the matching network, require significant tuning time when changing the frequency This is contrary to the latest trends in the development of radio transmitting systems, which involve the use of fast frequency hopping to ensure the noise immunity of radio links. Thus, research on the development of matching methods and algorithms that will significantly reduce the matching time of the radio transmitting path is a relevant task.

The aim of the article is to study of the possibility of reducing the time of matching the antenna-feeder path with a HF radio transmitter using an automatic switching antenna-matching device by using machine learning and neural networks as an algorithm or part of an algorithm for determining the corresponding state of the matching network.

The article presents the implementation of the algorithm for matching the antenna-feeder path of the HF band of radio waves based on neural networks with the distribution of responsibility, as well as their architecture and methods for their training. The use of the presented algorithm makes it possible to significantly reduce the time for determining the state of the matching network of the antenna-matching device in order to achieve the best matching. The architecture of neural networks used in the proposed algorithm is adapted for implementation on low-power microcontrollers.

The work was carried out according to the state task of the Omsk Scientific Center SB RAS (project registration number 122011200349-3).

Pavlov A.P., Kashchenko I.E., Bakhmutskaya A.V. The algorithm of matching of the antenna-feeder path of HF radio waves based on neural networks with the distribution of responsibility zones. Radiotekhnika. 2022. V. 86. № 11. P. 178−188.
DOI: https://doi.org/10.18127/j00338486-202211-24 (In Russian)

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