Utilizing invariant shadow fading data for training a machine learning model
US12328604B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 25, 2022 |
| Grant date | Jun 10, 2025 |
| Priority date | — |
| Expiry date | Oct 26, 2043 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04W24/08
- WIPO fieldDigital communication
- WIPO sectorElectrical engineering
Abstract
A device may receive real mobile radio data identifying measurements of radio transmissions of base stations and user devices of a mobile radio environment in a geographical area, and may receive network topology data associated with the geographical area. The device may utilize, based on the network topology data, a machine learning feature extraction approach to generate a representation of invariant aspects of spatiotemporal predictable components of the real mobile radio data, and may generate, based on the representation of invariant aspects, stochastic data that includes a probability that a radio signal will be obstructed. The device may utilize the stochastic data to identify a realistic discoverable spatiotemporal signature, and may train or evaluate a system to manage performance of a mobile radio network based on the realistic discoverable spatiotemporal signature.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.