This paper proposes a deep learning-based design scheme for ultra-long distance communication transmission systems in ultra-high voltage engineering projects,aiming to enhance the reliability of signal transmission and strengthen the robustness against complex transmission environments.Initially,an attention mechanism is introduced to dynamically focus on different parts of the signal,achieving adaptive encoding.Subsequently,a self-supervised learning technique is employed to learn effective features from a vast amount of unlabeled data,enabling transmission status prediction and allowing the system to quickly adapt to complex transmission environments.Results demonstrate that the system has achieved significant improvements in both signal processing efficiency and transmission reliability,providing an efficient and reliable solution for ultra-long distance communication transmission in ultra-high voltage engineering.
关键词
深度学习/超长距通信传输/注意力机制/自监督学习
Key words
deep learning/ultra-long distance communication transmission/attention mechanism/SSL
维普
万方数据