Artificial Intelligence-Empowered Hybrid Multiple-Input/Multiple-Output Beamforming: Learning to Optimize for High-Throughput Scalable MIMO-Reference-Cited by-同舟云学术

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Artificial Intelligence-Empowered Hybrid Multiple-Input/Multiple-Output Beamforming: Learning to Optimize for High-Throughput Scalable MIMO

Published:2024 Issue: Volume: Page:2-11
ISSN:1556-6072
Container-title:IEEE Vehicular Technology Magazine
language:
Short-container-title:IEEE Veh. Technol. Mag.

Author:

Shlezinger Nir¹^ORCID,Ma Mengyuan²^ORCID,Lavi Ortal¹^ORCID,Nguyen Nhan Thanh³^ORCID,Eldar Yonina C.⁴^ORCID,Juntti Markku³^ORCID

Affiliation:

1. School of Electrical and Computer Engineering, Ben-Gurion University, Be’er Sheva, Israel

2. Centre for Wireless Communications, University of Oulu, Oulu, Finland

3. University of Oulu, Oulu, Finland

4. Department of Math and Computer Science, Weizmann Institute of Science, Rehovot, Israel

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/10209/6354260/10535041.pdf?arnumber=10535041

Cited by 1 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. Sum-Rate Maximization for a Hybrid Precoding-Based Massive MIMO NOMA System with Simultaneous Wireless Information and Power Transmission;Telecom;2024-09-02

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