UE Application Data Filtering for Radio-Efficient Network Analytics
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Solution Overview
Problem
Current network configurations in wireless communication networks fail to efficiently match radio resource usage with diverse application demands due to a lack of detailed knowledge about traffic flows, particularly in supporting uplink and downlink streams.
Innovation Solution
Implementing a method where a base station transmits network configuration information to a UE application, which filters application data based on network conditions and application requirements, using AI applications like machine learning, and adjusts filtering configurations during training or inference phases.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If network configuration information is transmitted to UE application for data filtering, then radio efficiency is improved and processing needs are reduced, but device complexity and network complexity increase
Solution Approach 1:
The patent introduces an intermediary filtering mechanism where the UE application acts as a mediator between the data source and the network. The UE application filters application data based on received filtering configurations before transmission, reducing the data load on the network while maintaining selective data transmission capabilities.
Solution Approach 2:
The patent segments the data filtering function into separate components: the filtering configuration is generated by the network based on traffic flow knowledge, transmitted to the UE application, which then independently applies the filtering rules. This segmentation allows complex filtering logic to be distributed rather than centralized.
2Quantity of substance
If filtering configuration is transmitted from base station to UE application, then data transfer is optimized and bandwidth is reduced, but loss of information may occur
Solution Approach 1:
The patent changes the parameters of data transmission by applying filtering rules that selectively modify which data packets are transmitted. The filtering configuration includes parameters such as data types, priorities, and conditions that determine transmission, allowing optimization of data volume while preserving critical information through configurable filtering criteria.
3Adaptability or versatility
If AI applications are used for adaptive filtering, then adaptability to diverse application demands is improved, but device complexity and processing requirements increase
Solution Approach 1:
The patent implements a self-service mechanism where the UE application autonomously applies filtering configurations received from the network without requiring continuous network control or complex centralized processing. The UE application independently evaluates data against filtering rules and makes transmission decisions, reducing the processing burden on network infrastructure.
Solution Approach 2:
The patent uses parameter-based filtering configurations that can be dynamically adjusted by the network based on AI analysis of traffic patterns. These parameters are transmitted to the UE application, which adapts its filtering behavior by changing operational parameters rather than requiring complex structural modifications, achieving adaptability with manageable complexity.
Data Source
AI summary
A method in a telecommunications system including a Data Network, DN, a base station, a connection via the base station from the DN to a User Equipment, UE, executing a UE application producing application data, and an algorithm entity on the DN, wherein the base station transmits network configuration information to a DN application executing on the algorithm entity, the DN application produces and transmits a filtering configuration based on the network configuration information to the UE for use in filtering the application data before transmission to the algorithm entity, allowing the UE to produce application data filtered according to the filtering configuration, and the connection transmits the filtered application data to the algorithm entity.