Deep Unsupervised Learning for Joint Antenna Selection and Hybrid Beamforming-Reference-Cited by-同舟云学术

Deep Unsupervised Learning for Joint Antenna Selection and Hybrid Beamforming

Published:2022-03 Issue:3 Volume:70 Page:1697-1710
ISSN:0090-6778
Container-title:IEEE Transactions on Communications
language:
Short-container-title:IEEE Trans. Commun.

Author:

Liu Zhiyan¹^ORCID,Yang Yuwen¹^ORCID,Gao Feifei¹^ORCID,Zhou Ting²^ORCID,Ma Hongbing³

Affiliation:

1. State Key Laboratory of Intelligent Technologies and Systems, Institute for Artificial Intelligence Tsinghua University (THUAI), and the Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China

2. Shanghai Frontier Innovation Research Institute, Chinese Academy of Sciences, Shanghai, China

3. Department of Electronic Engineering, Tsinghua University, Beijing, China

Funder

National Natural Science Foundation of China

Tsinghua University Initiative Scientific Research Program

Tsinghua University-China Mobile Communications Group Co., Ltd. Joint Institute

Science and Technology Commission Foundation of Shanghai

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/26/9736381/09681824.pdf?arnumber=9681824

Reference57 articles.

1. Deep Learning for Distributed Channel Feedback and Multiuser Precoding in FDD Massive MIMO

2. Antenna selection in massive MIMO systems: Full-array selection or subarray selection?

3. Machine Learning-Enabled Joint Antenna Selection and Precoding Design: From Offline Complexity to Online Performance

4. Joint Antenna Selection and Hybrid Beamformer Design Using Unquantized and Quantized Deep Learning Networks

5. Learning-Based Antenna Selection for Multicasting

Cited by 26 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Inverse design of a novel multiport power divider based on hybrid neural network;Concurrency and Computation: Practice and Experience;2024-09-11

2. Risk-Aware Antenna Selection for Multiuser Massive MIMO Under Incomplete CSI;IEEE Transactions on Wireless Communications;2024-09

3. Artificial Intelligence for Wireless Physical-Layer Technologies (AI4PHY): A Comprehensive Survey;IEEE Transactions on Cognitive Communications and Networking;2024-06

4. A Graph and Number Theory Based Description Method and Equivalence Judgment of Power Electronics Topology;IEEE Transactions on Power Electronics;2024-05

5. Learning Energy-Efficient Transmitter Configurations for Massive MIMO Beamforming;IEEE Transactions on Machine Learning in Communications and Networking;2024