ASSESSMENT OF IMPORTANCE INDICATORS OF DATA TRANSMISSION CHANNELS OF SATELLITE COMMUNICATION SYSTEMS

DOI: 10.31673/2412-4338.2025.012360

Abstract

The task of determining the priority of satellite data transmission channels is relevant and has significant scientific and applied interest. The work establishes criteria for assessing the importance, which will allow determining the most informative channels for priority monitoring.The purpose of this work is to improve information technologies for assessing the importance of data transmission channels of satellite communication systems. Assessment of the energy availability of satellite communication systems is a key aspect for ensuring reliable and efficient communication. This process includes an analysis of the energy balance between the transmitter and the receiver, taking into account signal losses during its propagation through the atmosphere and outer space. The developed system of indicators of the importance of data transmission channels of satellite communication systems allows taking into account all key aspects of the availability and informativeness of channels. For practical use, it is proposed to create an expert system that will use fuzzy logic methods to take into account uncertainties. Creation of a methodology for determining the importance of transmission channels, based on the theory of fuzzy logic, methods of expert analysis and utility assessment. The work proposes to integrate all the proposed indicators into one generalized criterion of importance, which can be used for optimal allocation of resources when searching and monitoring satellite communication systems. The proposed system of indicators must be taken into account to assess the importance of data transmission channels of satellite communication systems during radio monitoring, to take into account dynamic changes in real-time conditions. Keywords: information technologies, data transmission channels, radio monitoring, remote methods. satellite communication systems, expert analysis methods, fuzzy logic methods.