Verizon Patent and Licensing Inc.

Hector A Garcia Crespo

Matthew Kapala

Brian A Ward

Brent D Segner

Timothy E Coyle

Sudha Subramaniam

Jason A Birr

Ricardo Francisco Borges

Dean P Jarski

Eric Freeman

Jacob S Lynch

Mark David Lufburrow

Ammara Essa

In some aspects, the techniques described herein relate to a method including: receiving an identity of fraudulent user equipment (UE); identifying a plurality of candidate UEs based on locations associated with the fraudulent UE and a duration of a session of the fraudulent UE; computing vectors representing the plurality of candidate UEs based on activity data associated with the plurality of candidate UEs recorded during the duration; comparing the plurality of vectors to a vector associated with activity data associated with the fraudulent UE to compute distances between the plurality of candidate UEs and the fraudulent UE; sorting the plurality of candidate UEs based on the distances; storing a top subset of the plurality of candidate UEs as co-located UEs; and performing an action using the top subset of the plurality of candidate UEs.

System and method for identifying collocated cellular devices from known fraudulent devices

A device may receive time domain PRB data associated with a plurality of base stations of a network, and may transform the time domain PRB data into frequency domain PRB data. The device may identify, based on the frequency domain PRB data, periodic interference patterns associated with the network, and may process periodic data associated with the periodic interference patterns, with a clustering model, to identify clusters of periodic interference patterns. The device may utilize a time offset analysis to link clusters and identify a transient periodic interferer, and may process cluster data associated with the clusters and the transient periodic interferer, and public transportation data, with a machine learning model, to predict a route associated with the transient periodic interferer. The device may perform one or more actions based on the route associated with the transient periodic interferer.

Systems and methods for detecting and mitigating periodic and transient interference in a network

A device may determine that a first geographical area satisfies an area threshold. The first geographical area includes an estimated location of a source of interference associated with base stations. A first plurality of vertices, of the first geographical area, are based on locations of the base stations. The device may determine a second plurality of vertices. The second plurality of vertices are closer to the estimated location than the first plurality of vertices. The device may provide information regarding the second plurality of vertices and may obtain magnitude information indicating magnitudes of the interference measured at the second plurality of vertices. The device may determine a third plurality of vertices based on the magnitude information. The device may provide information regarding a second geographical area, formed by the third plurality of vertices, to cause a search of the second geographical area to identify the source of the interference.

Systems and methods for determining a source of interference based on current measurements of a measurement device

Systems described herein may allow for the intelligent configuration of containers onto virtualized resources. Different configurations may be generated based on the simulation of alternate placements of containers onto nodes, where the placement of a particular container onto a particular node may serve as a root for several branches which may themselves simulate the placement of additional containers on the node (in addition to the container(s) indicated in the root). Once a set of configurations are generated, a particular configuration may be selected according to determined selection parameters and/or intelligent selection techniques.

Systems and methods for virtual machine resource optimization using tree traversal techniques representing alternate configurations

An interference detection system in a network identifies a first wireless station that has experienced radio frequency (RF) interference from an unknown source on at least one physical resource block (PRB) by determining that a key performance indicator (KPI) for the at least one PRB on the first wireless station has a value indicative of interference. The interference detection system identifies one or more second wireless stations that have experienced similar interference on the at least one PRB. A plurality of estimated interference source locations are determined based at least on geographic locations of the first wireless station and the one or more second wireless stations. Determining the plurality of estimated interference source locations further comprises generating a boundary based on the geographic locations of the first wireless station and the one or more second wireless stations and selecting a plurality of estimated interference source locations within the boundary.

Systems and methods for identifying a source of radio frequency interference in a wireless network

Systems described herein may allow for the intelligent configuration of containers onto virtualized resources. As described, systems described herein may generate configurations based on received parameters for utilization to configure (e.g., install, instantiate, etc.) virtualized resources. Once generated, a configuration may be selected according to determined selection parameters and/or intelligent selection techniques.

Systems and methods for virtual machine resource optimization using machine learning techniques

An interference detection system in a network identifies a first wireless station that has experienced radio frequency (RF) interference from an unknown source on at least one physical resource block (PRB) and identifies one or more second wireless stations that have experienced similar interference on the at least one PRB. A plurality of estimated interference source locations are determined based at least on geographic locations of the first wireless station and the one or more second wireless stations. The plurality of estimated interference source locations are scored based on a comparison of estimate interference to observed interference at the one or more second wireless stations and a geographical map is generated based on the scored plurality of estimated interference source locations, wherein the geographical map includes indicia indicative of the relative scores of the plurality of estimated interference source locations.

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Waltham, MA, United States of America

Hector A Garcia Crespo