Method and apparatus employing distributed sensing and deep learning for dynamic spectrum access and spectrum sharing
US12067487B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 21, 2020 |
| Grant date | Aug 20, 2024 |
| Priority date | — |
| Expiry date | Jun 22, 2043 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04W16/14
- WIPO fieldDigital communication
- WIPO sectorElectrical engineering
Abstract
The present application describes a method for training a neural network via deep reinforcement learning (DRL) in a RF network. The method includes a step of receiving, via the neural network, a policy from a third party. The method also includes a step of receiving, via the neural network, features of plural telecommunication groups located in an RF network. The method also includes a step of observing, via the neural network, a graphical representation of the received features of the plural telecommunication groups in the RF network. The method further includes a step of assigning, based on the observation, one of the plural telecommunication groups to one of plural channels in the RF network. The method even further includes a step of determining, via the neural network, a change in throughput of the RF network based on the assignment. The method yet even further incudes as step of adjusting, based on the determined change in throughput, the policy received from the third party.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.