M.A. Romashchenko1, D.V. Vasil’chenko2, D.A. Puhov3, M.E. Puhov4
1-4 FSBEI of HE “Voronezh State Technical University” (Voronezh, Russia)
1,4 kipr@vorstu.ru; 2 shadow951@bk.ru; 3 puhov.dm22@yandex.ru
Problem Statement. When operating robotic vehicles in dynamically changing electromagnetic environments, control channel quality may deteriorate, resulting in a reduced signal-to-noise ratio, an increased probability of packet erroneous reception, and increased data transmission delays. This necessitates the development of a methodology that enables adaptive reconfiguration of radio channel parameters, taking into account the current state of the propagation environment.
Purpose. To develop a methodology for ensuring noise-immune control of robotic platforms.
Results. A methodology for ensuring noise-immune control of robotic vehicles is proposed. This methodology is based on two-position spectral monitoring of the electromagnetic environment at transmission and reception points. A structural diagram of the methodology has been developed, including assessment of the electromagnetic environment, generation of a control channel state vector, calculation of a communication quality indicator, determination of the need for reconfiguration, and coordinated reconfiguration of radio channel parameters, followed by verification.
Romashchenko M.A., Vasil’chenko D.V., Puhov D.A., Puhov M.E. Methodology for ensuring interference-resistant control of robotic // Radiotekhnika. 2026. V. 90. № 7. P. 40−44. DOI: https://doi.org/10.18127/j00338486-202607-07
- Ghanaatian R., Afisiadis O., Cotting M., Burg A. LoRa digital receiver analysis and implementation. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 2019. P. 1498–1502. DOI:10.1109/ICASSP.2019.8683504.
- McCoy J., Rawat D.B. Software-defined networking for unmanned aerial vehicular networking and security: a survey. Electronics. 2019. V. 8. № 12. Р. 1468. DOI: 10.3390/electronics8121468.
- Pinto M.F., Marcato A.L.M., Melo A.G., Honório L.M., Urdiales C. A framework for analyzing fog-cloud computing cooperation applied to information processing of UAVs. Wireless Communications and Mobile Computing. 2018. V. 2019. Article ID 7497924. 14 p. DOI: 10.48550/arXiv.1901.03385.

