Automated Test Location Selection for Wireless Network Rollouts

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Solution Overview

Problem

Cellular network rollouts face challenges due to the complexity and diversity of networks, making it difficult to predict performance impacts during field testing, which can lead to service quality degradation and require extensive testing to ensure smooth deployment.

Innovation Solution

An automated method for selecting test locations based on features like software/hardware configuration, radio parameters, user population, and mobility patterns to improve predictability between field testing and network-wide deployment, reducing the number of test cases and identifying significant features affecting performance.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If extensive field testing is conducted to ensure network upgrade reliability, then service quality degradation is reduced, but time-to-market and deployment speed increase

Engineering Contradiction:

Improveservice qualityVSAvoidtime-to-market

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system performs preliminary analysis of network features and test location selection before conducting field tests. By pre-identifying significant features and optimal test locations using automated analysis, the system reduces the scope and duration of required field testing, thereby maintaining reliability while reducing time-to-market

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system changes the parameters of field testing by using automated test location selection based on diverse network features. This transforms the testing approach from exhaustive to targeted, selecting test locations that maximize the information gained about performance impacts while minimizing the number of test cases required

Inventive Principle:

Principle #35Parameter changes

2Device complexity

If small-scale field testing is used to reduce testing complexity, then deployment speed increases, but predictability of network-wide performance impacts decreases

Engineering Contradiction:

Improvetesting complexityVSAvoidpredictability

Core Design Contradiction:

Device complexityVSMeasurement precision

Solution Approach 1:

The system applies local quality by selecting specific test locations that represent different network characteristics and conditions. Rather than uniform random sampling, the automated selection identifies locations with diverse features (software/hardware configuration, radio parameters, user population, mobility patterns) that locally capture the variability of the entire network, improving predictability from small-scale tests

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The system changes the approach to testing by using automated analysis to identify and prioritize significant network features. This transforms small-scale testing from potentially unrepresentative to highly informative by ensuring test locations exhibit the key feature combinations that determine network-wide performance

Inventive Principle:

Principle #35Parameter changes

3Measurement precision

If automated test location selection based on diverse features is implemented, then predictability of performance impacts improves, but system complexity increases

Engineering Contradiction:

ImprovepredictabilityVSAvoidsystem complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system applies self-service by using automated analysis to perform test location selection without requiring manual expert intervention. The automated system independently analyzes network features, identifies significant parameters, and selects optimal test locations, reducing the complexity burden on human operators while maintaining high predictability

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system replaces manual mechanical processes (expert analysis and manual test location selection) with automated computational methods. This substitution handles the complexity of analyzing diverse network features and selecting optimal test locations through automated algorithms rather than human effort

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS10299140B2Change roll out in wireless networks

Publication Date: 2019.05.21 AT&T INTELLECTUAL PROPERTY I L P

AI summary

An approach for change roll out in wireless networks that utilizes a diverse set of features, such as software/hardware configuration, radio parameters, user population, mobility patterns, network topology and automatically identifies the test locations that would improve the predictability between the performance impacts during testing and network-wide deployment. Through automated and effective analysis of a wide variety of features, the approach for change roll out in wireless networks reflects the impacts observed during testing and predicts the performance of the post-test wide-scale deployment.