Machine learning based channel precoder selection for downlink
US12224885B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 10, 2023 |
| Grant date | Feb 11, 2025 |
| Priority date | — |
| Expiry date | Aug 10, 2043 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04W72/1273
- WIPO fieldDigital communication
- WIPO sectorElectrical engineering
Abstract
Methods, systems, and devices for wireless communications are described. A user equipment (UE) may transmit neural network (NN) capability information to a network entity. The network entity may train the NN model by selecting a NN-based precoder and generating associated coefficients. The network entity may transmit an indication of the precoder coefficients to the UE. The network entity may transmit demodulation reference signals (DMRSs) that have not been precoded and a physical downlink shared channel (PDSCH) signal that has been narrowband-precoded according to the indicated precoder. The UE may then perform and input a channel estimation to the NN model. The NN model may output the narrowband precoder, which the UE may use to generate a narrowband channel estimate and demodulate the narrowband precoded PDSCH signal. In some examples, the network entity may update NN coefficients and may indicate the updated NN coefficients to the UE.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.