View source for US Patent Application 18143437. METHOD AND ELECTRONIC DEVICE FOR BUILDING DIGITAL TWIN BASED ON DATA OF BASE STATION IN COMMERCIAL NETWOR simplified abstract

=METHOD AND ELECTRONIC DEVICE FOR BUILDING DIGITAL TWIN BASED ON DATA OF BASE STATION IN COMMERCIAL NETWOR=


==Organization Name==

[[Samsung Electronics Co., Ltd.]]


==Inventor(s)==

[[Yujin Nam of Suwon-si (KR)]]

[[Seungmo Kim of Suwon-si (KR)]]

[[Haksung Kim of Suwon-si (KR)]]

[[Seowoo Jang of Suwon-si (KR)]]

[[Gyeongmin Pyeon of Suwon-si (KR)]]

==METHOD AND ELECTRONIC DEVICE FOR BUILDING DIGITAL TWIN BASED ON DATA OF BASE STATION IN COMMERCIAL NETWOR - A simplified explanation of the abstract==


This abstract first appeared for US patent application 18143437 titled 'METHOD AND ELECTRONIC DEVICE FOR BUILDING DIGITAL TWIN BASED ON DATA OF BASE STATION IN COMMERCIAL NETWOR

==Simplified Explanation==

The patent application describes an electronic device with a memory, transceiver, and processor.
* The device receives base station data and divides it into smaller pieces according to a first time unit.
* It then combines these pieces to generate first data for the first time unit.
* The first data is further divided into smaller time intervals according to a second time interval unit.
* The device calculates probability density functions for each of these time intervals.
* It generates representative data using these probability density functions.
* Finally, the device uses the representative data to train a base station model.


==Original Abstract Submitted==

An electronic device includes a memory storing instructions, a transceiver configured to receive base station data, and at least one processor configured to execute the instructions to: divide the base station data into a plurality of pieces of base station data according to a first time unit; generate first data of the first time unit by superimposing the plurality of pieces of base station data on each other; divide the first data of the first time unit into a plurality of second time intervals, according to a second time interval unit; calculate at least one probability density function for each second time interval of the plurality of second time intervals; generate at least one first representative data by using respective probability density functions of the plurality of second time intervals; and train the base station model, based on the at least one first representative data.