등록
무선 시스템에서 딥러닝 기반의 빔포밍 방안 및 그 장치
- 발명자
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홍승은, 이훈, 박석환, 김준범
- 출원번호
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17380826 (2021.07.20)
- 공개번호
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20220029665 (2022.01.27)
- 등록번호
- 11742901 (2023.08.29)
- 출원국
- 미국
- 협약과제
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20HH3200, 고밀집 네트워크(UDN) 환경에서 고용량, 저비용 달성을 위한 무선전송 기술 개발,
홍승은
- 초록
- 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.
- KSP 제안 키워드
- Activation function, Deep neural network(DNN), Feature Learning, Hidden layer, Input layer, Output layer, Power Limit, Transmit power, base station(BS), deep learning(DL), neural network, transmit antennas
- 패밀리
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