US 11,950,122 B2
Cleaning raw data generated by a telecommunications network for deployment in a deep neural network model
Sayed Taheri, Cheshire (GB); Faris Muhammad, Edgware (GB); Hamed Al-Raweshidy, New Denham (GB); and Srini Challa, Hatfield (GB)
Assigned to VIAVI Solutions Inc., Chandler, AZ (US)
Filed by VIAVI Solutions Inc., San Jose, CA (US)
Filed on Oct. 1, 2021, as Appl. No. 17/492,144.
Prior Publication US 2023/0107148 A1, Apr. 6, 2023
Int. Cl. H04W 24/10 (2009.01); G06F 18/21 (2023.01); G06F 18/214 (2023.01); G06F 40/143 (2020.01); G06F 40/289 (2020.01); G06N 3/04 (2023.01); G06N 3/08 (2023.01); H04W 24/08 (2009.01)
CPC H04W 24/10 (2013.01) [G06F 18/214 (2023.01); G06F 18/217 (2023.01); G06F 40/143 (2020.01); G06F 40/289 (2020.01); G06N 3/04 (2013.01); G06N 3/08 (2013.01); H04W 24/08 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method, comprising:
receiving, by a device, software logs identifying raw data generated by a telecommunications network;
converting, by the device, the raw data from a markup language format to a text format, to generate text data;
changing, by the device, name strings of the text data to a new name;
extracting, by the device, pre-log data, associated with test cases, from the text data;
removing, by the device, files with less than a threshold quantity of lines from the text data to generate modified text data;
extracting, by the device, user equipment (UE) data, associated with a particular quantity of UEs, from the modified text data;
decoding, by the device, radio resource control (RRC) messages in the modified text data to generate decoded RRC messages;
extracting, by the device, marker data, associated with particular markers, from the modified text data;
removing, by the device, files associated with timestamps and a first set of the test cases from the modified text data to generate further modified text data;
extracting, by the device, test case data, associated with a second set of the test cases, from the further modified text data;
generating, by the device, final data with the new name and including the pre-log data, the UE data, the decoded RRC messages, the marker data, and the test case data; and
training, by the device, a deep neural network (DNN) model with the final data to generate a trained DNN model.