User Scheduling in Massive MIMO: A Joint Deep Learning and Genetic Algorithm Approach-Reference-Cited by-同舟云学术

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User Scheduling in Massive MIMO: A Joint Deep Learning and Genetic Algorithm Approach

Published:2022-06 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE 95th Vehicular Technology Conference: (VTC2022-Spring)
language:
Short-container-title:

Author:

Mohammadkarimi Mostafa¹,Darabi Mostafa²,Maham Behrouz³

Affiliation:

1. Delft University of Technology,Faculty of Electrical Engineering, Mathematics and Computer Science,Netherlands

2. University of British Colombia,Department of Electrical and Computer Engineering,Canada

3. Nazarbayev University,School of Engineering and Digital Sciences,Department of ECE,Kazakhstan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9860273/9860350/09860903.pdf?arnumber=9860903

Reference19 articles.

1. A Genetic Algorithm-Based Antenna Selection Approach for Large-but-Finite MIMO Networks

2. Intelligent Massive MIMO Antenna Selection Using Monte Carlo Tree Search

3. 5G MIMO Data for Machine Learning: Application to Beam-Selection Using Deep Learning

4. MmWave Vehicular Beam Selection With Situational Awareness Using Machine Learning

5. Beam Selection in mm-Wave Multiuser MIMO Systems Using Compressive Sensing

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. Learning User Scheduling and Hybrid Precoding with Sequential Graph Neural Network;2024 IEEE Wireless Communications and Networking Conference (WCNC);2024-04-21

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