Calibrating Network Performance Metrics Using Passive Measurement Data
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Solution Overview
Problem
Wireless network providers face challenges in accurately measuring network performance due to variability in testing methods, particularly with background active measurement (BAM) tests, which can be influenced by high network demand and user activities, leading to biased results that do not reflect real network activity.
Innovation Solution
A data calibration system that weights BAM test results based on passively collected data usage to minimize bias and improve measurement accuracy by applying weights calculated from passive measurement data, ensuring that BAM test results align with expected usage patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If background active measurement (BAM) tests are conducted to measure network performance, then network performance data can be collected, but the results become biased due to high network demand and user activities
Solution Approach 1:
The patent introduces an intermediary calibration process that uses passively collected data as a mediator to adjust and correct the actively collected BAM test results. The passive data serves as an unbiased reference that mediates between the biased active measurements and the true network performance, allowing correction of measurement biases without requiring changes to the underlying measurement infrastructure.
Solution Approach 2:
The patent changes the parameters of the measurement system by collecting data through multiple methods (active BAM testing and passive collection) with different characteristics, then adjusts the parameters of the final performance metrics through calibration. The calibration process modifies the active measurement results by applying correction factors derived from passive data, effectively changing the measurement parameters to eliminate bias.
2Measurement precision
If passive measurement data is collected to calibrate BAM results, then measurement accuracy improves, but data collection and processing complexity increases
Solution Approach 1:
The patent implements a universal calibration framework that can be applied across multiple networks, markets, and device types. The calibration process uses a standardized approach that works with different combinations of active and passive data sources, making the system multi-functional and adaptable to various scenarios without requiring separate calibration systems for each case.
Solution Approach 2:
The calibration system is designed to be self-adjusting, where the passive measurement data automatically provides the correction information needed to calibrate the active BAM results. The system uses the collected passive data to generate calibration factors and apply corrections without requiring external intervention or complex manual adjustment processes.
Data Source
AI summary
Methods, apparatus, systems, and articles of manufacture to calibrate payload information are disclosed. An example apparatus includes at least one memory, instructions in the apparatus, and processor circuitry. The processor circuitry is to execute the instructions to obtain (a) passive measurement data and (b) background active measurement (BAM) data from panelists in a market of interest, the BAM data associated with network usage metrics of panelist wireless devices undisturbed by panelist behavior. The processor circuitry is also to execute the instructions to assign a first share of the passive measurement data and a second share of the BAM data to particular areas within the market of interest, the first share based on a number of passive measurement occurrences in a first one of the particular areas, the second share based on a number of BAM occurrences in the first one of the particular areas. The processor circuitry is also to execute the instructions to remove a bias between the passive measurement data and the BAM data by calibrating the BAM data for the market of interest using weights determined for the first one of the particular areas based on the first and second shares.