Cellular Network Performance Management via Traffic Trace Correlation
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Solution Overview
Problem
Current performance management systems for cellular mobile data networks lack the ability to provide detailed, user-perceived end-to-end performance metrics on a cell-level basis, are not scalable, and are vendor-dependent, making it difficult for operators to identify and address performance issues effectively.
Innovation Solution
A method that captures raw traffic traces from standardized interfaces, builds a traffic and session database, defines key performance indicators, and calculates user-perceived quality metrics to characterize cell performance, enabling efficient performance management across cellular mobile packet data networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If passive measurement based characterization methods are used to analyze end-to-end performance, then user perceived quality can be determined, but detailed cell-level performance metrics cannot be obtained
Solution Approach 1:
The patent segments the network performance analysis by capturing traffic traces at multiple standardized interfaces (Gb, Gi, Gn, Gr) and correlating them with cell-level location information. This segmentation allows simultaneous measurement of end-to-end user perceived quality and detailed cell-level performance metrics by dividing the monitoring function across multiple measurement points in the network
Solution Approach 2:
The patent adds a spatial dimension to performance measurement by incorporating cell-level location information into the traffic trace correlation process. This enables the system to provide both end-to-end performance metrics and cell-specific performance data simultaneously, transforming the measurement from a network-wide aggregate view to a multi-dimensional view that includes geographic and cellular context
2Measurement precision
If drive tests are used to obtain cell-level performance results, then detailed cell performance can be measured, but the method is not scalable and generates additional network load
Solution Approach 1:
The patent implements self-service by utilizing existing network traffic and signaling that naturally flows through the network, rather than introducing external test traffic. The system correlates routinely captured traffic traces with cell-level location information from existing network signaling, eliminating the need for separate drive tests while maintaining scalability and avoiding additional network load
Solution Approach 2:
The patent creates a universal performance measurement system that works across multiple network interfaces and scenarios. By capturing and correlating traces from standardized interfaces (Gb, Gi, Gn, Gr), the system provides cell-level performance measurement that is applicable to various network conditions and traffic types without requiring specialized test equipment or procedures
3Loss of information
If performance counters from base station systems are used, then cell-level traffic load information can be obtained, but user perceived end-to-end quality metrics are not provided
Solution Approach 1:
The patent merges two previously separate measurement approaches by combining cell-level traffic counter data from base station systems with end-to-end user perceived quality measurements from traffic trace correlation. The system correlates traffic traces with cell-level location information and combines this with existing performance counters, providing both cell-level traffic load information and user perceived quality metrics in a unified measurement framework
4Measurement precision
If detailed traffic trace capture and correlation is implemented across multiple interfaces, then cell-level user perceived quality metrics can be calculated, but system complexity increases
Solution Approach 1:
The patent segments the complex measurement task by capturing traffic traces at multiple standardized interfaces (Gb, Gi, Gn, Gr) separately and then correlating them using cell-level location information as the key. This segmentation approach manages system complexity by dividing the measurement function across standard network components while maintaining the capability to calculate detailed cell-level user perceived quality metrics through systematic correlation of the segmented data
Data Source
AI summary
A method in a cellular mobile packet data network is provided composed of four main steps. These are capturing raw traffic traces over standardized interfaces of an operational cellular mobile data network, parsing through the traces in order to extract and correlate all the information, which is needed to build a traffic and session database, defining a set of appropriate key performance indicators, and calculating the above defined key performance indicators. A system in a mobile data network is also provided, the key element of which is a traffic and session database, which correlates traffic and mobility information extracted from passively captured traces collected from standardized interfaces. A set of key performance indicators describing the true, user perceived end-to-end quality of the most commonly used applications is also listed.