Abstract:
Unmanned Aerial Vehicle (UAV) network has excellent mobility and flexibility, and can efficiently perform various complex tasks. However, UAV are highly dynamic, which ca...Show MoreMetadata
Abstract:
Unmanned Aerial Vehicle (UAV) network has excellent mobility and flexibility, and can efficiently perform various complex tasks. However, UAV are highly dynamic, which causes the network topology to change frequently. In order to solve the above problems, this paper presents a topology prediction method of UAV network based on the space-time attention mechanism graph convolution network. This method utilizes the historical state information of each node in the network to predict its future connectivity. Compared to conventional approaches, our proposed method demonstrates improved accuracy and stability.
Published in: 2024 4th International Conference on Electronics, Circuits and Information Engineering (ECIE)
Date of Conference: 24-26 May 2024
Date Added to IEEE Xplore: 13 August 2024
ISBN Information:
School of Information and Electronics Beijing, Beijing Institute of Technology, China
School of Information and Electronics Beijing, Beijing Institute of Technology, China
School of Information and Electronics Beijing, Beijing Institute of Technology, China
School of Integrated Circuits and Electronics Beijing, Beijing Institute of Technology, China
Contents School of Information and Electronics Beijing, Beijing Institute of Technology, China
School of Information and Electronics Beijing, Beijing Institute of Technology, China
School of Information and Electronics Beijing, Beijing Institute of Technology, China
School of Integrated Circuits and Electronics Beijing, Beijing Institute of Technology, China
