Reinforcement learning (RL) and graph neural network (GNN)-based resource management for wireless access networks
US12245052B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 23, 2021 |
| Grant date | Mar 4, 2025 |
| Priority date | — |
| Expiry date | Jul 6, 2043 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L43/20
- WIPO fieldDigital communication
- WIPO sectorElectrical engineering
Abstract
A computing node to implement an RL management entity in an NG wireless network includes a NIC and processing circuitry coupled to the NIC. The processing circuitry is configured to generate a plurality of network measurements for a corresponding plurality of network functions. The functions are configured as a plurality of ML models forming a multi-level hierarchy. Control signaling from an ML model of the plurality is decoded, the ML model being at a predetermined level (e.g., a lowest level) in the hierarchy. The control signaling is responsive to a corresponding network measurement and at least second control signaling from a second ML model at a level that is higher than the predetermined level. A plurality of reward functions is generated for training the ML models, based on the control signaling from the MLO model at the predetermined level in the multi-level hierarchy.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.