Spectrum Access

Dynamic spectrum access (DSA) aims to improve wireless spectrum utilization by allowing secondary users to opportunistically access unoccupied frequencies. Current research focuses on developing intelligent algorithms, often employing deep learning (e.g., convolutional neural networks, vision transformers, and multi-agent reinforcement learning) and federated learning techniques, to optimize spectrum sharing and mitigate interference while addressing data privacy concerns. These advancements are crucial for enhancing the efficiency and reliability of future wireless communication systems, particularly in 6G and beyond, enabling applications like autonomous driving and federated learning in diverse environments.