Spectrum Management

Spectrum management aims to optimize the use of radio frequencies, addressing scarcity and interference issues to maximize network efficiency and user experience. Current research heavily utilizes machine learning, particularly reinforcement learning and deep learning models (e.g., Soft Actor-Critic, Support Vector Machines), to dynamically allocate spectrum resources, classify signals, and predict network demand, often within the framework of open radio access networks (O-RAN). These advancements improve spectrum utilization, enhance network performance, and enable more efficient spectrum auctions, impacting both the design of wireless communication systems and regulatory processes.