Apparatus, method and computer program for accelerating grid-of-beams optimization with transfer learning
US12400116B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | May 26, 2021 |
| Grant date | Aug 26, 2025 |
| Priority date | — |
| Expiry date | Aug 24, 2042 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04B7/0617
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A deep transfer reinforcement learning (DTRL) method based on transfer learning within a deep reinforcement learning (DRL) framework is provided to accelerate the GoB optimization decisions when experiencing environment changes in the same source radio network agent or when being applied from a source radio network agent to a target radio network agent. The transferability of the knowledge embedded in a pre-trained neural network model as a Q-approximator is exploited, and a mechanism to transfer parameters from a source agent to a target agent is provided, where the transferability criterion is based on the similarity measure between the source and target domain.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.