The problems of modern spectrum management are being solved increasingly by using artificial intelligence (AI) and big data technologies. The rapid development of wireless communication systems such as mobile networks, IoT devices, and satellite communication has significantly increased the demand for limited radio frequency spectrum resources. Conventional spectrum management techniques involve manual oversight and fixed allocation policies that are inefficient for managing dynamic and extensive spectrum environments. This work proposes a framework combining Big Data analytics and AI techniques to enhance the efficiency of spectrum monitoring, analysis and allocation. The system examines real-time and historical frequency information to detect interference, predict spectrum usage and optimize resource utilization. We have built a prototype web-based platform to help regulatory authorities with real-time dashboards, predictive analytics and other tools.
Reddy et al. (Fri,) studied this question.