US 12,192,806 B2
Predictive modeling of energy consumption in a cellular network
Harish Arunachalam, Frisco, TX (US); Neil Singh Sethi, Jersey City, NJ (US); Martin Konkel, Madison, NJ (US); Robert Belson, New York, NY (US); and Patrick Wagstrom, Coventry, CT (US)
Assigned to Verizon Patent and Licensing Inc., Basking Ridge, NJ (US)
Filed by VERIZON PATENT AND LICENSING INC., Basking Ridge, NJ (US)
Filed on Nov. 22, 2021, as Appl. No. 17/531,847.
Prior Publication US 2023/0164599 A1, May 25, 2023
Int. Cl. H04W 24/08 (2009.01); H04W 84/04 (2009.01)
CPC H04W 24/08 (2013.01) [H04W 84/042 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method comprising:
receiving raw data from a plurality of data sources, the raw data collected while operating a cellular network;
normalizing the raw data based on a set of logical cell sites (LCSs) in the cellular network to generate per-LCS data;
generating an example from the per-LCS data, the example associated with a given LCS in the set of LCSs;
generating a predicted energy consumption value for the given LCS by inputting the example into a predictive model;
determining that the predicted energy consumption value is higher than an expected energy consumption value associated with the given LCS; and
labeling the given LCS as an outlier.