/Protocol And Signaling Framework Enabling Machine Learning Models In Wireless Communication Networks
Abstract
Aspects of the subject disclosure may be directed to, for example, a method including determining a set of data collection parameters that are configurable to collect data indicative of network events occurring in real time or near real time in the wireless communication networks, receiving the collected data based on the set of data collection parameters from a group of network entities operating in the wireless communication networks, based on the received collected data, and generating training data for a machine learning model deployed in the wireless communication networks. Other embodiments are disclosed.
Full Text
What is claimed is:
Aspects of the subject disclosure may be directed to, for example, a method including determining a set of data collection parameters that are configurable to collect data indicative of network events occurring in real time or near real time in the wireless communication networks, receiving the collected data based on the set of data collection parameters from a group of network entities operating in the wireless communication networks, based on the received collected data, and generating training data for a machine learning model deployed in the wireless communication networks. Other embodiments are disclosed.
Timeline
Filed
06/15/2026Published
10/01/2026Granted
Not AvailableIPC Codes(3)
H04L 67/12:specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
H04W 28/02:Traffic management, e.g. flow control or congestion control
H04W 72/30:Resource management for broadcast services