A Semi-Supervised Modulation Identification in MIMO Systems: A Deep Learning Strategy-Reference-Cited by-同舟云学术

A Semi-Supervised Modulation Identification in MIMO Systems: A Deep Learning Strategy

Published:2022 Issue: Volume:10 Page:76622-76635
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Bouchenak Sofya¹,Merzougui Rachid¹^ORCID,Harrou Fouzi²^ORCID,Dairi Abdelkader³^ORCID,Sun Ying²^ORCID

Affiliation:

1. STIC Laboratory, Faculty of Engineering Science of Tlemcen, Tlemcen, Algeria

2. Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia

3. Université des Sciences et de la Technologie d’Oran Mohamed-Boudiaf (USTOMB), Oran, Algeria

Funder

King Abdullah University of Science and Technology (KAUST), Office of Sponsored Research

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09832883.pdf?arnumber=9832883

Reference70 articles.

1. Automatic Modulation Recognition Using Deep Learning Architectures

2. End-to-End Learning From Spectrum Data: A Deep Learning Approach for Wireless Signal Identification in Spectrum Monitoring Applications

3. An ensemble automatic modulation classification model with weight pruning and data preprocessing;yang,2020

4. Deep Learning-Based Cooperative Automatic Modulation Classification Method for MIMO Systems

5. Modulation Classification in MIMO Systems With Distribution Test Ensemble

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