AI-Driven spectrum sensing in cognitive radio networks

The proliferation of wireless devices and applications has led to a significant increase in the demand for radio frequency spectrum. Traditional static spectrum allocation methods result in inefficient spectrum usage. Cognitive Radio (CR) technology offers a dynamic spectrum access solution, enabling secondary users to opportunistically utilize underutilized spectrum bands without causing interference to primary users. The integration of Artificial Intelligence (AI) into cognitive radio sensing enhances its capability to efficiently and accurately detect spectrum opportunities. This paper explores the principles, techniques, and challenges of AI-based cognitive radio sensing, highlighting the transformative impact of AI on spectrum management. AI-Based Cognitive Radio Sensing utilizes advanced machine learning techniques to enhance the spectrum detection performance of cognitive radios.