Deep Learning Empowered Semi-Blind Joint Detection in Cooperative NOMA

Deep Learning Empowered Semi-Blind Joint Detection in Cooperative NOMA

In this paper, we propose a multi-user symbol detection in cooperative-non-orthogonal multiple access (C-NOMA) schemes via deep learning (DL). We use a DL-based detection (DLDet) in both users instead of conventional detectors. Therefore, an iterative detector (i.e., successive interference canceler...

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Bibliographic Details
Main Authors: Ahmet Emir, Ferdi Kara, Hakan Kaya, Halim Yanikomeroglu
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Cooperative NOMA
deep learning
error performance
joint symbol detection
semi-blind detection
Online Access:https://ieeexplore.ieee.org/document/9409081/

Internet

https://ieeexplore.ieee.org/document/9409081/

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