An intent-driven 6g network intelligent operation and maintenance method, system, device and application

Abstract

The present invention belongs to the technical field of wireless communication, and discloses an intention-driven 6G network intelligent operation and maintenance method, system and application. The intention-driven 6G network intelligent operation and maintenance method translates the original operator's intention represented by natural language into Network-recognizable intent standard expression; through the intent intelligent strategy generation module, the intelligent reorganization of fine-grained strategies is realized, and intelligent new strategies that meet the intent are generated; the deep neural evolution network is introduced to perform feature extraction on the collected fault information set, and the fault Type, location, quantity, fault source information and fault occurrence time, and construct network fault topology map for fault location and repair. The introduction of AI in the present invention transforms network operation and maintenance from manual to intelligent. The application of intelligent technologies such as machine learning enables the network to detect and repair network faults in a timely manner, guarantees the self-driving, self-optimizing and robustness of the network, and improves network management efficiency.

Description

technical field [0001] The invention belongs to the technical field of wireless communication, and in particular relates to a method, system, equipment and application for intentionally driving 6G network intelligent operation and maintenance. Background technique [0002] At present: Public security operates key businesses on the IT network system, so whether the system can run normally is directly related to the key to whether the business can run normally. However, with the continuous increase of network devices and the increasingly complex network structure, network operation and maintenance are also facing great challenges. Before a network fault occurs, it is impossible to predict the network fault in time; at the same time, after the fault occurs, it is impossible to respond to the fault in a timely manner. It is necessary to artificially analyze the fault and find an effective solution and compensation method. Network operation and maintenance delays are high, manua...

AI Technical Summary

Problems solved by technology

[0004] (1) The means of network operation and maintenance are backward: traditional network operation and maintenance is mainly performed by operation and maintenance personnel based on their own experience and knowledge. It takes a long time for newcomers to accumulate knowledge and experience

At the same time, the network operation and maintenance at the current stage lacks predictive measures, and it is impossible to find problems in the first place. It only seeks effective methods to solve and make up for the faults that have occurred, and it is impossible to predict the faults in advance.

[0005] (2) The network operation and maintenance system is not perfect: In the traditional network operation and maintenance mode, equipment and personnel are relatively scattered and managed separately. The experience and knowledge of operation and maintenance personnel cannot be dimension inefficiency

At the same time, there are many uncertain factors in the occurrence of network failures. The operation and maintenance personnel cannot immediately notify the operation and maintenance personnel of the problems existing in the network, and the operation and maintenance personnel cannot respond to the network problems in the first time.

Network operation and maintenance delays are large, and network failures cannot be handled in time

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