Deep Learning for Energy Efficient Beamforming in MU-MISO Networks: A GAT-Based Approach-Reference-Cited by-同舟云学术

Deep Learning for Energy Efficient Beamforming in MU-MISO Networks: A GAT-Based Approach

Published:2023-07 Issue:7 Volume:12 Page:1264-1268
ISSN:2162-2337
Container-title:IEEE Wireless Communications Letters
language:
Short-container-title:IEEE Wireless Commun. Lett.

Author:

Li Yuhang¹,Lu Yang¹^ORCID,Zhang Ruichen¹^ORCID,Ai Bo²^ORCID,Zhong Zhangdui³^ORCID

Affiliation:

1. School of Computer and Information Technology and the Collaborative Innovation Center of Railway Traffic Safety, Beijing Jiaotong University, Beijing, China

2. State Key Laboratory of Rail Traffic Control and Safety and the School of Electronics and Information Engineering, Beijing Jiaotong University, Beijing, China

3. State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China

Funder

Fundamental Research Funds for the Central Universities

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Beijing Nova Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/5962382/10177762/10108002.pdf?arnumber=10108002