INFORMATION TECHNOLOGY OF DYNAMIC FREQUENCY RESOURCE MANAGEMENT IN COMPLEX RADIO-ELECTRONIC ENVIRONMENT

The article proposes an advanced information technology for dynamic frequency resource management under complex radio-electronic conditions, where spectrum scarcity, high user density, and intentional electronic countermeasures create critical challenges. The developed model integrates the flexibility of software-defined radio (SDR) with the adaptive intelligence of cognitive radio, enabling autonomous detection of free frequency bands, resistance to interference, and rapid reconfiguration of transmission parameters. The functional basis of the approach is the “observation–analysis–decision–adaptation” cycle, which has been implemented in the GNU Radio environment with the use of SDR platforms such as USRP. Within this framework, the system continuously monitors the radio spectrum, applies spectral analysis methods, and adapts transmission according to real-time assessments of interference and noise levels. Special emphasis is given to the application of machine learning algorithms, including Q-learning, which provide the system with the capability to accumulate operational experience and improve decision-making efficiency in highly dynamic environments. Such mechanisms ensure a re