BROWSE
Detail
Registered DEEP LEARNING BASED BEAMFORMING METHOD AND APPARATUS
- Inventors
- Hong Seung Eun, 이훈, 박석환, 김준범
- Application No.
- 17380826 (2021.07.20)
- Publication No.
- 20220029665 (2022.01.27)
- Registration No.
- 11742901 (2023.08.29)
- Country
- UNITED STATES
- Project Code
- 20HH3200, Development of Radio Transmission Technologies for High Capacity and Low Cost in Ultra Dense Networks, Hong Seung Eun
- Abstract
- Disclosed is a beamforming method using a deep neural network. The deep neural network may include an input layer, L hidden layers, and an output layer, and the beamforming method may include: obtaining channel information h between a base station and K terminals and a transmit power limit value P of the base station, and inputting h and P into the input layer; and performing beamforming on signals to be transmitted to the K terminals using beamforming vectors derived using the output layer and at least one activation function, wherein the base station transmits the signals to the K terminals using M transmit antennas. Here, the output layer may be configured in a direct beamforming learning (DBL) scheme, a feature learning (FL) scheme, or a simplified feature learning (SFL) scheme.
- Family
| Status | Patent | Country | KIPRIS |
|---|---|---|---|
| Registered | Deep learning based beamforming method and apparatus for the same | KOREA | KIPRIS |