US 12,225,388 B1
Machine learning-based system, method, and computer program for making a 5G private network deployment recommendation
Jean-marc Eric Ohayon, Givat Shmuel (IL); and Gil Mazurik, Hod Hasharon (IL)
Assigned to AMDOCS DEVELOPMENT LIMITED, Limassol (CY)
Filed by Amdocs Development Limited, Limassol (CY)
Filed on Aug. 24, 2021, as Appl. No. 17/410,894.
Int. Cl. H04W 16/18 (2009.01); G06N 5/04 (2023.01); H04W 16/14 (2009.01); H04W 48/18 (2009.01)
CPC H04W 16/18 (2013.01) [G06N 5/04 (2013.01); H04W 16/14 (2013.01); H04W 48/18 (2013.01)] 19 Claims
OG exemplary drawing
 
1. A non-transitory computer-readable media storing computer instructions which when executed by one or more processors of a device cause the device to:
obtain input that defines a plurality of parameter values associated with an enterprise for which a 5G private network is to be deployed, wherein the plurality of parameter values include at least:
characteristics of the enterprise,
quality of service requirements for the 5G private network, and
capabilities of the 5G private network;
process the plurality of parameter values by a machine learning model to infer, for the enterprise, an optimal deployment scenario for the 5G private network, wherein the optimal deployment scenario is selected by the machine learning model from among a plurality of available deployment scenarios that are existing deployment configurations for use in implementing 5G private networks;
output an indication of the optimal deployment scenario as a recommendation for deploying the 5G private network for the enterprise;
select a network service from a catalog of network services that is configured to deploy the optimal deployment scenario; and
initiate the network service to deploy the optimal deployment scenario for the enterprise.