Novel Multilayer Extreme Learning Machine as a Massive MIMO Receiver for Millimeter Wave Communications-Reference-Cited by-同舟云学术

Novel Multilayer Extreme Learning Machine as a Massive MIMO Receiver for Millimeter Wave Communications

Published:2022 Issue: Volume:10 Page:58965-58981
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Carrera Diego Fernando¹^ORCID,Vargas-Rosales Cesar²^ORCID,Zabala-Blanco David³^ORCID,Yungaicela-Naula Noe M.²^ORCID,Azurdia-Meza Cesar A.⁴^ORCID,Marey Mohamed⁵^ORCID,Firoozabadi Ali Dehghan⁶^ORCID

Affiliation:

1. School of Technologies, Universidad Tecnológica Empresarial de Guayaquil, Guayaquil, Ecuador

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

3. Department of Computer Science and Industry, Universidad Catolica del Maule, Talca, Chile

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

5. Smart Systems Engineering Laboratory, College of Engineering, Prince Sultan University, Riyadh, Saudi Arabia

6. Department of Electricity, Universidad Tecnologica Metropolitana, Santiago, Chile

Funder

Secretaría de Educación Pública (SEP), Consejo Nacional de Ciencia y Tecnología (CONACyT) Research Project

School of Engineering and Sciences and the Telecommunications Research Focus Group with the Tecnologico de Monterrey

Proyect Fondo Nacional de Desarrollo Científico y Tecnológico

Proyect Agencia Nacional de Investigación y Desarrollo (ANID) FONDECYT

Laboratory of Technological Research in Pattern Recognition

Internal

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09784835.pdf?arnumber=9784835

Reference66 articles.

1. Dimension Reduction With Extreme Learning Machine

2. Representational learning with extreme learning machine for big data;kasun;IEEE Intell Syst,2013

3. Optimal Multiuser Transmit Beamforming: A Difficult Problem with a Simple Solution Structure [Lecture Notes]

4. Toward Massive MIMO 2.0: Understanding Spatial Correlation, Interference Suppression, and Pilot Contamination

5. A Comparative Performance Analysis of Extreme Learning Machine and Echo State Network for Wireless Channel Prediction

Cited by 6 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. Four port tri-circular ring MIMO antenna with wide-band characteristics for future 5G and mmWave applications;Heliyon;2024-04

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

3. IQM Mitigation Algorithm with Channel Awareness for Upstream SC-FDMA Systems in the Context of Dual-Hop Broadcasts;Applied Sciences;2023-05-09

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

5. Coded Assisted Transmit and Receive IQ Mismatch Compensation With Channel Estimation for AF Cooperative OFDM Systems;IEEE Access;2023