5G signals detection using neural network
US11026198B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 16, 2019 |
| Grant date | Jun 1, 2021 |
| Priority date | — |
| Expiry date | Nov 20, 2039 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04W88/06
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A communication system that includes neural network system configured to learn from training examples of radio frequency (RF) signals, and circuitry configured to label a first set of fifth generation (5G) RF signals originated from a first type of source and a second set of 5G RF signals originated from a second type of source. At least one RF impairment is added randomly to each labelled example of the first set of 5G RF signals and the second set of 5G RF signals, wherein randomization of artificially added RF impairment to each labeled example corresponds to addition of different RF impairments randomly to different labeled examples. The neural network system is trained with a plurality of labelled examples. Each labelled example includes an artificially added RF impairment. The circuitry uses the trained neural network system to detect an input 5G RF signal having a new RF impairment.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.