Receiver Design for ICI-CSK System: A New Perspective Based on GRU Neural Network-Reference-Cited by-同舟云学术

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Receiver Design for ICI-CSK System: A New Perspective Based on GRU Neural Network

Published:2023-11 Issue:11 Volume:27 Page:2983-2987
ISSN:1089-7798
Container-title:IEEE Communications Letters
language:
Short-container-title:IEEE Commun. Lett.

Author:

Zou Jian¹^ORCID,Tao Yiwei²^ORCID,Fang Yi¹^ORCID,Ma Huan³^ORCID,Yang Zhaojie⁴^ORCID

Affiliation:

1. School of Information Engineering, Guangdong University of Technology, Guangzhou, China

2. School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China

3. Electronics and Information Engineering Department, Zhaoqing University, Zhaoqing, China

4. School of Electrical and Electronic Engineering, Nanyang Technological University, Jurong West, Singapore

Funder

NSF of China

Basic and Applied Basic Research Foundation of Guangdong Province

National Research Foundation, Singapore and Infocomm Media Development Authority under its Future Communications Research and Development Programme

International Collaborative Research Program of Guangdong Science and Technology Department

Industrial Research and Development Project of Haoyang Electronic Company Ltd.

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Modeling and Simulation

Link

http://xplorestaging.ieee.org/ielx7/4234/10314840/10255727.pdf?arnumber=10255727

Reference21 articles.

1. Intelligent and Reliable Deep Learning LSTM Neural Networks-Based OFDM-DCSK Demodulation Design

2. Design of Divide-and-Conquer Noise Decontamination Strategy for M-Ary DCSK: From Remodulation to Denoising

3. Reliable and Secure Deep Learning-Based OFDM-DCSK Transceiver Design Without Delivery of Reference Chaotic Sequences

4. An Intelligent Detection Based on Deep Learning for Multilevel Code Shifted Differential Chaos Shift Keying System With M-ary Modulation

5. Data-Driven Deep Learning for Automatic Modulation Recognition in Cognitive Radios

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