US 11,812,290 B2
Using machine learning to optimize wireless carrier system testing
Peter P. Myron, Fall City, WA (US); and Michael J. Mitchell, North Bend, WA (US)
Assigned to T-Mobile USA, Inc., Bellevue, WA (US)
Filed by T-Mobile USA, Inc., Bellevue, WA (US)
Filed on Dec. 20, 2021, as Appl. No. 17/555,770.
Prior Publication US 2023/0199530 A1, Jun. 22, 2023
Int. Cl. H04W 24/06 (2009.01)
CPC H04W 24/06 (2013.01) 18 Claims
OG exemplary drawing
 
1. A computer-implemented method comprising:
executing a first test of a suite of tests that are to be executed for testing one or more components of a system operated by a wireless carrier;
providing, as input to a trained machine learning model, data generated as a result of executing the first test;
classifying, using the trained machine learning model, and based at least in part on the data, a second test of the suite of tests as a test that is likely to pass when executed;
and modifying the suite of tests by refraining from executing the second test;
wherein the data comprises performance data indicative of a performance of the one or more components; wherein the performance data indicates whether the one or more components interacted with a predefined set of other components or systems as a result of executing the first test.