Method for non-linear distortion immune end-to-end learning with autoencoder—OFDM
US11570030B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 8, 2020 |
| Grant date | Jan 31, 2023 |
| Priority date | — |
| Expiry date | Oct 24, 2040 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04L27/2615
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A new layer tailored for Artificial Intelligence-based communication systems to limit the instantaneous peak power for the signals that relies on manipulation of complementary sequences through neural networks. Disclosed is a method for providing non-linear distortion in end-to-end learning communication systems, the communication system comprising a transmitter and a receiver. The method includes mapping transmitted information bits to an input of a first neural network; controlling, by an output of the neural network, parameters of a complementary sequence (CS) encoder, producing an encoded CS; transmitting the encoded CS through an orthogonal frequency division multiplexing (OFDM) signal; processing, by Discrete Fourier Transform (DFT), the encoded CS, to produce a received information signal in a frequency domain; and processing, by a second neural network, the received information signal.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.