Machine learning (ML)-based dynamic demodulator parameter selection
US12279208B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 23, 2022 |
| Grant date | Apr 15, 2025 |
| Priority date | — |
| Expiry date | Aug 24, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/02
- WIPO fieldDigital communication
- WIPO sectorElectrical engineering
Abstract
A method of wireless communication by a receiver, includes predicting, with an artificial neural network, at each data block of a set of data blocks, a least complex set of demodulator parameters that will achieve a goal, based on features of a data block expected to be received. The method also includes dynamically selecting the least complex set of demodulator parameters, from multiple sets of demodulator parameters, based on the features of the data block expected to be received. The selecting occurring to prevent degradation of demodulation performance for each data block with the selected set of demodulator parameters for the data block, with respect to a more complex set of demodulator parameters.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.