Federated learning for client-specific neural network parameter generation for wireless communication
US11909482B2 · kind B2 · utility
1Cited by
39References
30Claims
0Family size
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Key dates
| Filing date | Jul 29, 2021 |
| Grant date | Feb 20, 2024 |
| Priority date | — |
| Expiry date | Dec 16, 2041 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04B7/0663
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a client may determine, using a conditioning network and based at least in part on an observed environmental vector, a set of client-specific parameters. The client may determine a latent vector using a client autoencoder and based at least in part on the set of client-specific parameters and the set of shared parameters. The client may transmit the observed environmental vector and the latent vector to a server. Numerous other aspects are provided.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.