Research Article
Research on Active Disturbance Rejection Method of Mobile Communication Network Nodes Based on Artificial Intelligence
@INPROCEEDINGS{10.1007/978-3-030-67874-6_5, author={Bing Li and Feng Jin and Ying Li}, title={Research on Active Disturbance Rejection Method of Mobile Communication Network Nodes Based on Artificial Intelligence}, proceedings={Advanced Hybrid Information Processing. 4th EAI International Conference, ADHIP 2020, Binzhou, China, September 26-27, 2020, Proceedings, Part II}, proceedings_a={ADHIP PART 2}, year={2021}, month={1}, keywords={Artificial intelligence Mobile communication network Anti-interference Feature analysis}, doi={10.1007/978-3-030-67874-6_5} }- Bing Li
Feng Jin
Ying Li
Year: 2021
Research on Active Disturbance Rejection Method of Mobile Communication Network Nodes Based on Artificial Intelligence
ADHIP PART 2
Springer
DOI: 10.1007/978-3-030-67874-6_5
Abstract
With the increasingly complex network environment and the interference of various other radio waves, the quality of mobile communication network is seriously affected. Aiming at the above problems, this paper studies an auto-disturbance rejection method for mobile communication network nodes based on artificial intelligence. According to artificial intelligence, an interference identification analysis model is constructed, which is used to identify and analyze the interference factors of mobile communication network nodes. Based on the recognition results, the characteristics of different interference types are summarized, and the interference problem is accurately judged. Then, the anti-interference work of mobile communication network nodes is completed by checking and processing the results. The experimental results show that the user is more satisfied with the quality of the mobile communication processed by this method than the traditional method of UAI participating in the identification and analysis of interference factors, which proves that this method is effective in anti-jamming and can meet the needs of users.
