Analytics-Based Policy Generation for Dynamic Network Adaptation
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Solution Overview
Problem
Current wireless communication networks, particularly 4G, rely on static policy rules that do not adapt to dynamic user behavior, leading to suboptimal performance and user experience due to lack of real-time analytics-based policy generation.
Innovation Solution
The introduction of an analytics function within the policy framework that collects usage data from user equipment (UE) and network functions, applies analytics to identify trends, and dynamically generates network policies to optimize performance and user experience based on these trends.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If static policy rules are used in 4G networks, then network management is simple and reliable, but network performance and user experience become suboptimal due to inability to adapt to dynamic user behavior
Solution Approach 1:
The patent transforms static policy rules into dynamic policies that automatically adapt to changing user behavior patterns. The analytics function continuously monitors usage data and updates policies in real-time, enabling the network to respond dynamically to user needs while maintaining manageable complexity through automated decision-making algorithms.
Solution Approach 2:
The system implements a feedback loop where usage data is collected from the network, analyzed to identify user behavior patterns, and used to generate updated policies that are applied back to the network. This closed-loop feedback mechanism enables continuous optimization of network performance based on actual user behavior without requiring manual intervention.
2Productivity
If analytics-based policy generation is implemented, then network performance and user experience improve through real-time adaptation, but system complexity increases due to additional analytics processing requirements
Solution Approach 1:
The patent divides the complex analytics processing into distinct functional components: data collection from multiple sources, pattern recognition algorithms, policy generation modules, and policy enforcement mechanisms. This segmentation allows each component to be optimized independently and managed separately, reducing overall system complexity while maintaining high network performance.
Solution Approach 2:
The patent introduces an intermediary analytics function that acts as a bridge between raw usage data and policy decisions. This intermediary layer processes and interprets complex data patterns, transforming them into actionable policy rules that can be applied by the network, thereby simplifying the overall system architecture while enabling sophisticated performance optimization.
3Measurement precision
If usage data is collected from remote units, then accurate analytics and policy generation are enabled, but battery consumption and network overhead increase
Solution Approach 1:
The patent implements selective data collection where only relevant usage data parameters are monitored based on current network conditions and user behavior patterns. Rather than continuously collecting all possible data, the system collects partial data sets that are sufficient for accurate analytics while minimizing battery consumption and network overhead through intelligent parameter selection.
Data Source
AI summary
Apparatuses, methods, and systems are disclosed for analytics-based policy generation. One apparatus (500) includes a processor (505) and a radio transceiver (525) that communicates over a mobile communication network. The processor (505) receives a request from the mobile communication network to report at least one type of usage data according to a reporting policy, the at least one type of usage data including battery usage data and/or network location data. The processor (505) transmits (710) a usage report (225) containing the usage data based on the reporting policy. The processor (505) further receives (715) and applies (720) a network policy (240) from the mobile communication network. The network policy (240) is dynamically generated by the mobile communication network based on at least one trend identified in the usage data.