A Knowledge-Based Deep Learning Detection Scheme for Downlink SCMA Systems-Reference-Cited by-同舟云学术

A Knowledge-Based Deep Learning Detection Scheme for Downlink SCMA Systems

Published:2023-03 Issue:3 Volume:12 Page:486-490
ISSN:2162-2337
Container-title:IEEE Wireless Communications Letters
language:
Short-container-title:IEEE Wireless Commun. Lett.

Author:

Zheng Yu¹^ORCID,Hou Xiaoming¹^ORCID,Wang Hui¹^ORCID,Jiang Ming²^ORCID,Zhang Shengli¹^ORCID

Affiliation:

1. College of Electronics and Information Engineering, Shenzhen University, Shenzhen, China

2. Peng Cheng Laboratory, Shenzhen, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/5962382/10063957/09998063.pdf?arnumber=9998063

Reference25 articles.

1. On the Design of Near-Optimal Sparse Code Multiple Access Codebooks

2. SCMA Decoding via Deep Learning

3. DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators;lu;arXiv 1910 03193,2019

4. Efficient Sparse Code Multiple Access Decoder Based on Deterministic Message Passing Algorithm

5. A novel deep neural network based approach for sparse code multiple access

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