A Review of Sparse Code Multiple Access Based on Deep Learning

Author(s):  
Zhong Yu ◽  
Huiping Wang
Author(s):  
Sergio Vidal-Beltrán ◽  
José Luis López Bonilla ◽  
Fernando Martínez Piñón ◽  
Jesús Yalja-Montiel

Recently, technologies based on neural networks (NNs) and deep learning have improved in different areas of Science such as wireless communications. This study demonstrates the applicability of NN-based receivers for detecting and decoding sparse code multiple access (SCMA) codewords. The simulation results reveal that the proposed receiver provides highly accurate predictions based on new data. Moreover, the performance analysis results of the primary optimization algorithms used in machine learning are presented in this study.


2021 ◽  
pp. 108258
Author(s):  
Thi Ha Ly Dinh ◽  
Megumi Kaneko ◽  
Keisuke Wakao ◽  
Kenichi Kawamura ◽  
Takatsune Moriyama ◽  
...  

2021 ◽  
pp. 1-1
Author(s):  
Ibrahim Al-Nahhal ◽  
Octavia A. Dobre ◽  
Ertugrul Basar
Keyword(s):  

2018 ◽  
Vol 67 (9) ◽  
pp. 8440-8450 ◽  
Author(s):  
Guan Gui ◽  
Hongji Huang ◽  
Yiwei Song ◽  
Hikmet Sari

2017 ◽  
Vol 66 (11) ◽  
pp. 9986-9999 ◽  
Author(s):  
Jincheng Dai ◽  
Kai Niu ◽  
Chao Dong ◽  
Jiaru Lin

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