Wireless Signal Metadata Extraction for Efficient Data Analysis
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Solution Overview
Problem
Analyzing large amounts of wireless communication signal data is time-consuming and inefficient, especially when trying to identify specific issues or areas requiring additional resources, due to the complexity of modern wireless signals like OFDM.
Innovation Solution
A system that extracts metadata in real-time from wireless signal data, allowing for the identification and selection of portions with specific characteristics of interest, reducing the data to be processed and enabling faster analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all measurement data is analyzed to identify communication problems, then measurement precision is improved, but loss of time increases significantly
Solution Approach 1:
The patent extracts metadata from the captured signal data that characterizes specific features of interest (such as trigger conditions, signal properties, or events). This metadata is then analyzed separately to identify portions of the full data that contain communication problems, avoiding the need to analyze the entire large dataset and significantly reducing analysis time while maintaining problem detection accuracy.
Solution Approach 2:
The patent divides the analysis process into two segments: first analyzing a small subset of metadata to identify problematic time periods or signal portions, then focusing detailed analysis only on those specific segments. This segmentation allows efficient filtering of relevant data from the full capture, reducing overall analysis time while preserving measurement precision for the identified problems.
2Productivity
If trigger conditions are configured to capture only data of interest, then productivity is improved, but device complexity increases due to difficulty in setting up correct triggers
Solution Approach 1:
The system automatically extracts and analyzes metadata from the captured data to identify portions of interest without requiring manual trigger configuration. The metadata analysis performs self-service filtering by automatically characterizing the data and identifying problematic segments, eliminating the need for users to manually set complex trigger conditions while maintaining high productivity.
Solution Approach 2:
The patent performs preliminary extraction and analysis of metadata from the captured data before full analysis is attempted. This preliminary action identifies which portions of the data contain problems of interest, allowing the system to automatically determine the effective trigger conditions based on the actual data characteristics rather than requiring pre-configuration by the user.
3Ease of operation
If visual interpretation of time-domain representation is used to adjust triggers, then ease of operation is improved, but measurement precision deteriorates due to complexity of modern wireless signals
Solution Approach 1:
The patent introduces metadata as an intermediary between the raw captured signal and the trigger configuration. Instead of directly visualizing complex time-domain waveforms, the system extracts simplified metadata that characterizes signal features and problems. This metadata serves as an intermediate representation that is easier to interpret while preserving the information needed for accurate problem detection and trigger setting.
Data Source
AI summary
A system for analyzing data, such as data representing samples of a received wireless signal, includes a memory controller for storing the data in one or more memory devices, a metadata extractor for extracting metadata in real-time from the data as it is being processed for storage, and one or more processors for analyzing the metadata to identify portions of the stored data having a characteristic of interest, and for processing the identified portions of the stored data.