Spectrum Sharing
Spectrum sharing aims to optimize the use of limited radio frequencies by allowing multiple users or systems to concurrently access the same spectrum band. Current research heavily utilizes machine learning, particularly reinforcement learning and deep learning (including transformers and GANs), to dynamically allocate spectrum resources, often incorporating graph neural networks for efficient data processing and Bayesian optimization for autonomous resource management. This field is crucial for improving network capacity and efficiency in diverse applications, from 5G/6G networks and the Internet of Things to autonomous drone operations and vehicular communications, addressing both technical challenges and security/privacy concerns related to data sharing and spectrum access.
Papers
Spectrum Sharing between UAV-based Wireless Mesh Networks and Ground Networks
Zhiqing Wei, Zijun Guo, Zhiyong Feng, Jialin Zhu, Caijun Zhong, Qihui Wu, Huici Wu
The Performance Analysis of Spectrum Sharing between UAV enabled Wireless Mesh Networks and Ground Networks
Zhiqing Wei, Jialin Zhu, Zijun Guo, Fan Ning