Adaptive UE Policy Management for Private Network Provisioning
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Solution Overview
Problem
Enterprises face challenges in controlling and flexibly managing UEs within private networks due to intricate and rigid SIM provisioning processes, leading to inefficiencies in enforcing business policies, managing congestion, and scaling network infrastructure in response to demand fluctuations.
Innovation Solution
A management system that utilizes a machine learning model to process natural language UE policies, generate configuration scripts, and adapt policies in real-time based on monitoring data, enabling automated and adaptive UE management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional SIM provisioning processes are used, then network security and basic functionality are maintained, but control and flexibility over UEs are insufficient due to intricate and rigid processes
Solution Approach 1:
The patent extracts the complex SIM provisioning processes from the traditional network management system and replaces them with a simplified policy-based management approach. The management system separates UE management into policy definition, policy compilation to configuration scripts, and automated execution, removing the intricate procedural complexity while maintaining security and control.
Solution Approach 2:
The system changes the management paradigm from rigid procedural parameters to flexible policy parameters. Administrators can dynamically adjust UE management policies (such as network access, resource allocation, and service permissions) without modifying underlying provisioning processes, enabling adaptability while keeping the core system simple.
2Productivity
If manual UE management methods are used, then detailed control over each UE is possible, but resource consumption increases and scalability decreases
Solution Approach 1:
The management system implements self-service automation where configuration scripts are automatically generated, compiled, and executed based on policy definitions. The system autonomously manages UE provisioning, configuration updates, and policy enforcement without requiring manual intervention for each UE, thereby improving productivity while reducing computational overhead through automation efficiency.
Solution Approach 2:
The patent creates a universal configuration script generation mechanism that can manage multiple UEs with different policies using a single standardized process. The compilation system translates diverse policy requirements into统一的 configuration scripts, enabling efficient batch management of numerous UEs simultaneously, thus improving productivity without proportionally increasing resource consumption.
3Adaptability or versatility
If rigid provisioning processes are maintained, then system stability is preserved, but ability to rapidly scale up or down in response to demand fluctuations is hindered
Solution Approach 1:
The system introduces dynamic policy management where UE management configurations can be rapidly adjusted through policy updates rather than rigid provisioning changes. The compilation system dynamically generates updated configuration scripts based on new policies, enabling the network to scale up or down quickly in response to demand while maintaining stable core provisioning infrastructure.
Solution Approach 2:
The patent implements preliminary policy definition and configuration script compilation capabilities that prepare management configurations in advance. When demand fluctuations occur, pre-compiled configuration scripts and defined policies enable rapid deployment or decommissioning of UE services without ad-hoc provisioning processes, thus improving scalability while preserving system stability.
4Extent of automation
If automated policy management is implemented, then control and flexibility are enhanced, but complexity of policy processing and machine learning integration increases
Solution Approach 1:
The patent introduces a configuration script compilation system as an intermediary layer between high-level policy definitions and low-level UE configurations. This intermediary automatically translates administrator-defined policies into executable configuration scripts, automating the management process while containing complexity within the compilation mechanism rather than exposing it throughout the entire system architecture.
Data Source
AI summary
A device may receive a natural language user equipment (UE) policy for a UE associated with a private network, and may compile the natural language UE policy into a UE configuration script. The device may execute the UE configuration script to provision the UE relative to the private network, and may receive monitoring data identifying activities of the UE within the private network after execution of the UE configuration script. The device may process the monitoring data, with a machine learning model, to generate a new UE policy for the UE, and may update the UE configuration script based on the new UE policy and to generate an updated UE configuration script. The device may execute the updated UE configuration script to reprovision the UE relative to the private network.