METHODS FOR DETECTION AND ELIMINATION OF RADIO INTERFERENCE IN RADIO MONITORING SYSTEMS USING ARTIFICIAL INTELLIGENCE (Eureka Journal of Computing Science & Digital Innovation, 2026)
This scientific article considers the issues of using artificial intelligence methods in the detection, classification and elimination of radio interference in radio monitoring systems. The effectiveness of machine learning, deep neural networks, reinforcement learning and adaptive filtering algorithms is analyzed. The proposed approaches are aimed at increasing spectrum efficiency, improving signal quality and ensuring automatic control.Nowadays, radio communications, telecommunications, radar and wireless data transmission systems are developing rapidly. One of the main problems in these areas is radio interference (noise), which degrades signal quality, leads to data loss and reduces system reliability. Traditional filtering and signal processing methods do not always provide high efficiency. Therefore, the use of artificial intelligence (AI) technologies to eliminate radio interference is relevant.
Keywords: Radio monitoring, artificial intelligence, machine learning, neural network, radio interference, spectrum analysis, cognitive radio, 5G/6G.