公开(公告)号：US11304172B2

公开(公告)日：2022-04-12

申请号：US16867868

申请日：2020-05-06

申请人： AT&T Intellectual Property I, L.P.

发明人： Ronald Kiefer ,  Mario Kosseifi ,  Xiaodi Zhang ,  Kumar Vadlamudi ,  Badal Chowdhary

IPC分类号： H04W4/00 ,  H04W64/00 ,  H04W4/029 ,  G06N20/00 ,  H04W48/20 ,  H04W4/02

摘要： Crowd sourced data from mobile devices may be used to estimate site locations. In addition, machine learning models may be used to filter out any inaccurate crowd sourced data before using algorithms to estimate the cell site location. An apparatus may include a processor and a memory coupled with the processor that effectuates operations. The operations may include receiving data associated with a location of plurality of devices that have connected with a base station in a geographic area; determining a machine learning model to apply to the received data based on the type of data, wherein the machine learning model is a clustering model; performing the clustering model on the received data; based on the performing the clustering model on the received data, obtaining representative data that excludes outliers in the received data; based on the representative data, determining a location of the base station in the geographic area; and sending a message with the location of the base station.

公开(公告)号：US20210352609A1

公开(公告)日：2021-11-11

申请号：US16867868

申请日：2020-05-06

申请人： AT&T Intellectual Property I, L.P.

发明人： Ronald Kiefer ,  Mario Kosseifi ,  Xiaodi Zhang ,  Kumar Vadlamudi ,  Badal Chowdhary

IPC分类号： H04W64/00 ,  H04W4/029 ,  H04W4/02 ,  H04W48/20 ,  G06N20/00

摘要： Crowd sourced data from mobile devices may be used to estimate site locations. In addition, machine learning models may be used to filter out any inaccurate crowd sourced data before using algorithms to estimate the cell site location. An apparatus may include a processor and a memory coupled with the processor that effectuates operations. The operations may include receiving data associated with a location of plurality of devices that have connected with a base station in a geographic area; determining a machine learning model to apply to the received data based on the type of data, wherein the machine learning model is a clustering model; performing the clustering model on the received data; based on the performing the clustering model on the received data, obtaining representative data that excludes outliers in the received data; based on the representative data, determining a location of the base station in the geographic area; and sending a message with the location of the base station.