Automated Wireless Control Loop Goal Provisioning from Service Specifications
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Solution Overview
Problem
The determination of control loop goals for closed control loops in wireless communication systems requires human expertise, which is time-consuming and costly, and existing systems lack automation for deriving these goals from service specifications.
Innovation Solution
The system automatically determines control loop goals for closed control loops based on service specifications, using a mapping table or machine learning model, trained on historical data, to configure the loops without human intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual determination of control loop goals by skilled operators is used, then the accuracy and appropriateness of control loop configuration is improved, but the time consumption and operational cost increase
Solution Approach 1:
The system enables automatic determination of control loop goals through self-service mechanisms where the network management system autonomously generates control loop goals based on service specifications and historical data, eliminating the need for manual operator intervention while maintaining configuration accuracy
Solution Approach 2:
The system performs preliminary actions by pre-configuring control loop goals automatically before manual intervention is needed, using service specifications and machine learning models to prepare appropriate control parameters in advance, thus reducing the time required for actual deployment
2Reliability
If manual determination of control loop goals by skilled operators is used, then the configuration quality is improved, but the operational cost increases
Solution Approach 1:
The system implements self-service automation where the network management system automatically determines control loop goals using service specifications and trained machine learning models, eliminating the need for expensive skilled operator intervention while maintaining high configuration quality through algorithmic precision
Solution Approach 2:
The system uses copying by replicating successful control loop configurations from historical data and service specifications, allowing automatic generation of proven effective configurations without requiring repeated manual analysis by expensive skilled personnel
3Productivity
If automatic determination of control loop goals is implemented, then the speed of management operations is improved, but the need for skilled personnel decreases
Solution Approach 1:
The system achieves high-speed automatic determination through self-service mechanisms where the network management system autonomously processes service specifications and generates control loop goals using machine learning models, enabling rapid deployment without human intervention
Solution Approach 2:
The system replaces the mechanical process of manual operator analysis and configuration with automated computational processes using machine learning models and service specification parsing, dramatically increasing the speed of management operations while reducing dependency on human expertise
Data Source
AI summary
A closed control loop in a management domain of a communication system may be automatically configured by receiving a service specification, translating the service specification to produce a control loop goal configurable in the management domain, and configuring the closed control loop according to the control loop goal.


