무선 시스템에서 딥러닝 기반의 빔포밍 방안 및 그 장치
홍승은, 이훈, 박석환, 김준범
- 11742901 (2023.08.29)
20HH3200, 고밀집 네트워크(UDN) 환경에서 고용량, 저비용 달성을 위한 무선전송 기술 개발,
- 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