Utilizing machine learning models to estimate user device spatiotemporal behavior
US12250658B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 25, 2022 |
| Grant date | Mar 11, 2025 |
| Priority date | — |
| Expiry date | Jun 1, 2043 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04W24/10
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A device may receive a first type of data identifying measurements associated with user devices and/or base stations of a mobile radio environment, and a second type of data identifying spatiotemporal behavior associated with the user devices. The device may train a first model, with the first type of data, to generate a trained first model that yields dimensionality-reduced spatiotemporal characteristics of the first type of data, and may train a second model, with the second type of data and the dimensionality-reduced spatiotemporal characteristics, to generate a trained second model. The device may receive particular data identifying measurements associated with a user device and/or base stations, and may process the particular data, with the trained first model, to generate a dimensionality-reduced spatiotemporal characteristic of the particular data. The device may process the dimensionality-reduced spatiotemporal characteristic, with the trained second model, to predict a spatiotemporal behavior of the user device.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.