Core Network Policy Management for Reduced Capability Devices
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Solution Overview
Problem
Current network management systems face challenges in efficiently handling reduced capability devices (redcap devices) by failing to dynamically adjust protocols and policies, leading to suboptimal network performance and resource allocation.
Innovation Solution
The system identifies user devices as redcap devices, determines their specific type and data requirements, and implements tailored traffic steering policies on the network core using non-real-time radio intelligence controllers, optimizing network functions and resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If network management systems use static protocols and policies for all devices, then network complexity is reduced and ease of operation is improved, but network performance and resource allocation efficiency deteriorate when handling reduced capability devices
Solution Approach 1:
The patent segments network devices into different categories based on their capabilities, specifically identifying reduced capability devices (redcap devices) versus full-capability devices. This segmentation allows the network management system to apply different protocols and policies tailored to each device type, thereby improving resource allocation efficiency without overwhelming the system with excessive complexity. The segmentation is implemented through device identification mechanisms that classify devices based on their capability profiles.
Solution Approach 2:
The patent implements dynamic protocol and policy adjustment based on real-time device capability identification. Rather than using static configurations for all devices, the system dynamically adapts its behavior by detecting redcap devices and applying appropriate simplified protocols and resource allocation policies. This dynamic approach enables the network to optimize performance for different device types while maintaining manageable complexity through automated adaptation rules.
2Reliability
If the system implements tailored traffic steering policies for each redcap device type, then network performance and resource allocation are optimized, but system complexity and processing overhead increase
Solution Approach 1:
The patent applies local quality by implementing specific traffic steering policies tailored to each redcap device type based on its particular capabilities and requirements. Different device types receive customized protocol configurations and resource allocation strategies suited to their specific characteristics, thereby optimizing network performance for each category while avoiding the need for fully individualized complex policies for every single device.
Solution Approach 2:
The system changes key network parameters such as protocol selection, traffic steering rules, and resource allocation settings based on the identified device type. By dynamically adjusting these parameters according to device capability classifications, the system achieves optimized performance for redcap devices without requiring complete reconfiguration of the entire network architecture, thus managing complexity through targeted parameter modifications.
3Measurement precision
If the network identifies and categorizes each user device as a specific type of redcap device, then resource allocation accuracy is improved, but detection and measurement difficulty increases
Solution Approach 1:
The patent implements preliminary device capability identification and categorization during the device connection establishment phase, before full network operations begin. By performing device type detection and classification early in the connection process, the system accumulates necessary capability information that enables accurate subsequent resource allocation and protocol selection, thereby improving measurement precision while managing detection complexity through upfront classification.
Data Source
AI summary
Systems, methods, and computer-readable media herein dynamically adjust the policies used within a core network. These policies are determine based on the identification of a user device being a reduced capability device and the data requirements for that device. A correlation between the type of reduced capability device and the data requirements is used to derive data-drive insights using a non-real time RAN intelligence controller. The data used to determine these insights and policies are based on historical and non-real time sources.