To solve the problems of modern spectrum management, more and more people are using artificial intelligence (AI) and big data technologies. The fast growth of wireless communication systems like mobile networks, IoT devices, and satellite communication has made the need for limited radio frequency spectrum resources much greater. Conventional spectrum management techniques depend on manual oversight and fixed allocation policies, which are ineffective for managing dynamic and extensive spectrum environments. This research presents a framework that amalgamates Big Data analytics and AI methodologies to improve the efficiency of spectrum monitoring, analysis, and allocation. The system looks at both real-time and historical frequency data to find interference, guess how the spectrum will be used, and make the best use of resources. A prototype web-based platform is created to help regulatory authorities by giving them real-time dashboards, predictive analytics, and other tools.
Mrs.G.Vijayalaxmi et al. (Fri,) studied this question.