Extreme Learning Machine-Based Receiver for Multi-User Massive MIMO Systems-Reference-Cited by-同舟云学术

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Extreme Learning Machine-Based Receiver for Multi-User Massive MIMO Systems

Published:2021-02 Issue:2 Volume:25 Page:484-488
ISSN:1089-7798
Container-title:IEEE Communications Letters
language:
Short-container-title:IEEE Commun. Lett.

Author:

Carrera Diego Fernando¹^ORCID,Zabala-Blanco David²^ORCID,Vargas-Rosales Cesar¹^ORCID,Azurdia-Meza Cesar A.³^ORCID

Affiliation:

1. School of Engineering and Sciences, Tecnologico de Monterrey, Monterrey, Mexico

2. Department of Computing Science and Industry, Universidad Católica del Maule, Talca, Chile

3. Department of Electrical Engineering, Universidad de Chile, Santiago, Chile

Funder

Consejo Nacional de Ciencia y Tecnologa

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Modeling and Simulation

Link

http://xplorestaging.ieee.org/ielx7/4234/9352591/09223679.pdf?arnumber=9223679

Cited by 15 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. Receiver Metric Design for Short-Block Channels : A Perspective for Reliable 6G Signaling Scenarios;2024 Joint European Conference on Networks and Communications & 6G Summit (EuCNC/6G Summit);2024-06-03

2. A review on new technologies in 3GPP standards for 5G access and beyond;Computer Networks;2024-05

3. Evolution of RAN Architectures Toward 6G: Motivation, Development, and Enabling Technologies;IEEE Communications Surveys & Tutorials;2024

4. Binary MIMO Detection via Extreme Learning Machines in 5G Network and Beyond;2023 IEEE Globecom Workshops (GC Wkshps);2023-12-04

5. Residual Compensation-Based Extreme Learning Machine for MIMO-NOMA Receiver;IEEE Access;2023

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