Carrier aggregation optimization using machine learning
US11743878B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 30, 2022 |
| Grant date | Aug 29, 2023 |
| Priority date | — |
| Expiry date | Dec 30, 2042 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04W52/0258
- WIPO fieldDigital communication
- WIPO sectorElectrical engineering
Abstract
Various aspects of the present disclosure generally relate to wireless communication. In some aspects, an apparatus of a user equipment (UE) may determine a set of inputs to a neural network configured to predict radio frequency channel conditions or a user context associated with the UE. In some aspects, the set of inputs includes historical data related to a wireless environment, a communication pattern, or a behavior pattern associated with the UE. The apparatus of the UE may determine, using the neural network and based at least in part on the set of inputs, an optimal number of aggregated carriers to maximize one or more of a power parameter or a performance parameter. The apparatus of the UE may communicate using the optimal number of aggregated carriers. Numerous other aspects are described.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.