UE-Centric Carrier Aggregation Analytics for Anomaly Detection
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Solution Overview
Problem
Existing radio access network (RAN) data collection mechanisms fail to capture UE performance data suitable for determining sub-optimal user equipment (UE) experience with carrier aggregation (CA), leading to challenges in identifying and remediating issues such as incorrect configurations, abnormal UE behavior, and network congestion.
Innovation Solution
A system that collects and analyzes UE-centric data from multiple wireless network nodes to determine a target CA configuration and identify anomalies, using machine learning to distinguish between UE and base station issues, and applies remediation measures like software updates or configuration changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If RAN data collection mechanisms are used to capture cell site resource utilization, then cell site CA performance can be determined, but UE performance with regard to CA cannot be determined
Solution Approach 1:
The patent inverts the traditional cell-site-centric data collection approach by implementing a UE-centric data collection mechanism. Instead of collecting data only at the base station level, the system collects data directly from UEs including their CA configurations, actual throughput, and performance metrics. This inversion enables direct measurement of UE performance while maintaining cell site performance monitoring capabilities.
Solution Approach 2:
The patent introduces an intermediary data collection and correlation system that bridges the gap between RAN data collection mechanisms and UE performance determination. This intermediary component collects data from multiple sources including base stations, UEs, and core network elements, then correlates this data to determine both cell site and UE CA performance metrics simultaneously.
2Ease of operation
If traditional RAN data collection is used, then network operator control is maintained, but identification of sub-optimal UE experience with CA is not practical
Solution Approach 1:
The patent implements a universal data collection framework that serves multiple functions simultaneously: it collects data for both traditional cell site performance monitoring and new UE-centric CA performance analysis. The system can identify sub-optimal UE experiences while maintaining existing network operations, and can be extended to monitor other performance aspects beyond CA.
Solution Approach 2:
The patent segments the data collection and analysis functionality into distinct modular components: data collection modules at various network points, data correlation processing modules, and analysis modules for different performance metrics. This segmentation allows the system to add UE experience optimization capabilities without fundamentally redesigning the existing RAN data collection infrastructure.
3Measurement precision
If more data is collected from multiple network nodes, then UE-centric CA performance can be determined, but data processing complexity increases
Solution Approach 1:
The patent extracts only the essential UE-centric data elements needed for CA performance determination from the broader set of available network data. Instead of processing all possible network data, the system selectively collects and processes specific UE CA configuration data, throughput measurements, and radio conditions, reducing processing complexity while maintaining measurement precision.
Solution Approach 2:
The patent performs preliminary data filtering, validation, and formatting at the data collection points before data leaves the network nodes. This preliminary processing ensures that data is in the correct format and contains only relevant information before being transmitted to the central correlation system, significantly reducing the processing burden on downstream systems.
Data Source
AI summary
Carrier aggregation (CA) is optimized for user equipment (UE) experience. Various base station-centric data records from differing network nodes of a wireless network together identify: a set of layers available at a radio site, a downlink buffer size of a base station at the radio site for data to transmit to a UE, a CA capability of the UE, radio signal quality experienced by the UE, a set of radio layers used by the UE, throughput experienced by the UE, and other information. However, UE-centric information may be extracted and used to determine a target CA configuration for the UE and a target downlink throughput. By comparing the throughput experienced by the UE with the target downlink throughput, and the set of radio layers used by the UE with the target CA configuration for the UE, an anomalous CA condition may be identified and a remediation action determined.