Quantized Deep Learning Channel Model and Estimation for RIS-gMIMO Communication

Quantized Deep Learning Channel Model and Estimation for RIS-gMIMO Communication

Reconfigurable intelligent surfaces (RISs) and multiuser gigantic multiple-input multiple-output (MU-gMIMO) systems are key technologies for enabling sixth-generation (6G) networks. Their numerous advantages include minimal path losses, high energy efficiency (EE), high spectrum efficiency (SE), hig...

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Bibliographic Details
Main Authors: Joydev Ghosh, Cesar Vargas-Rosales, Van Nhan Vo, Chakchai So-In
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Open Journal of the Communications Society
Subjects:
Channel modeling
channel estimation
quantized deep learning (qDL)
reconfigurable intelligent surface (RIS)
multiuser gigantic multiple-input multiple-output (MU-gMIMO)
Online Access:https://ieeexplore.ieee.org/document/10737359/

Internet

https://ieeexplore.ieee.org/document/10737359/

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