公开(公告)号：US20240106731A1

公开(公告)日：2024-03-28

申请号：US17953507

申请日：2022-09-27

Applicant: AT&T Intellectual Property I, L.P.

Inventor： Masoor Ramesh ,  David Purdy ,  Frederick Farmer ,  Sean Simon

IPC: H04L43/50 ,  H04L41/16 ,  H04W24/04

CPC classification number: H04L43/50 ,  H04L41/16 ,  H04W24/04

Abstract: Aspects of the subject disclosure may include, for example, determining that one or more tests are to be executed for a core network of a telecommunications system, based on the determining, transmitting one or more test initiation commands to a set of user equipment (UEs) of a plurality of UEs communicatively coupled to the core network, wherein the one or more test initiation commands cause the set of UEs to execute the one or more tests, obtaining, from the set of UEs, results associated with the one or more tests, analyzing the results based on one or more machine learning (ML) models to identify a network issue, and responsive to the analyzing, performing one or more actions to address the network issue. Other embodiments are disclosed.

公开(公告)号：US20250080442A1

公开(公告)日：2025-03-06

申请号：US18475805

申请日：2023-09-27

Applicant: AT&T Intellectual Property I, L.P.

Inventor： Masoor Ramesh ,  Kim Haislip

IPC: H04L43/087 ,  H04L41/0681 ,  H04L43/0876

Abstract: Aspects of the subject disclosure may include, for example, accessing a heuristic rule associated with network data that is collectible by end user devices; determining a dynamic variable according to the heuristic rule; converting the dynamic variable to a value; adjusting, according to the value, a number of the end user devices that are to transmit the network data to a network device. Other embodiments are disclosed.

公开(公告)号：US20250077327A1

公开(公告)日：2025-03-06

申请号：US18475798

申请日：2023-09-27

Applicant: AT&T Intellectual Property I, L.P.

Inventor： Kim Haislip ,  Masoor Ramesh

IPC: G06F11/07

Abstract: Aspects of the subject disclosure may include, for example, obtaining training from wireless devices, where the wireless devices collect the training data that indicates first operational parameters and operational errors at the wireless devices; analyzing the training data to generate pre-failure thresholds according to the first operational parameters and the operational errors; receiving operational data from a particular wireless device, where the particular wireless device collects the operational data that indicates second operational parameters at the particular wireless device; analyzing the operational data according to the pre-failure thresholds resulting in a pre-failure analysis; and providing an alarm when the pre-failure analysis indicates that one or more of the second operational parameters violates one or more of the pre-failure thresholds, where the alarm is generated prior to a failure of the particular wireless devices that is predictable based on the second operational parameters. Other embodiments are disclosed.