Automatic Modulation Classification Based on Constellation Density Using Deep Learning

被引：97

作者：

Kumar, Yogesh ^{[1
]}

Sheoran, Manu ^{[1
]}

Jajoo, Gaurav ^{[1
]}

Yadav, Sandeep Kumar ^{[1
]}

机构：

[1] IIT Jodhpur, Dept Elect Engn, Jodhpur 342037, Rajasthan, India

来源：

IEEE COMMUNICATIONS LETTERS | 2020年 / 24卷 / 06期

关键词：

Feature extraction; Color; Phase shift keying; Signal to noise ratio; Training; Quadrature amplitude modulation; Modulation classification; deep learning; constellation; color image;

D O I：

10.1109/LCOMM.2020.2980840

中图分类号：

TN [电子技术、通信技术];

学科分类号：

0809 ;

摘要：

Deep learning (DL) is a newly addressed area of research in the field of modulation classification. In this letter, a constellation density matrix (CDM) based modulation classification algorithm is proposed to identify different orders of ASK, PSK, and QAM. CDM is formed through local density distribution of the signal's constellation generated using LabVIEW for a wide range of SNR. Two DL models, ResNet-50 and Inception ResNet V2 are trained through color images formed by filtering the CDM. Classification accuracy achieved demonstrates better performance compared to many existing classifiers in the literature.

引用

页码：1275 / 1278

页数：4

共 50 条

[1] Modulation Classification Based on Signal Constellation Diagrams and Deep Learning
Peng, Shengliang
Jiang, Hanyu
Wang, Huaxia
Alwageed, Hathal
Zhou, Yu
Sebdani, Marjan Mazrouei
Yao, Yu-Dong
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2019, 30 (03) : 718 - 727
[2] Deep Automatic Modulation Classification Using Deformation-Insensitive Color Constellation
Ding, Chaoren
Xu, Dongyang
2023 IEEE 97TH VEHICULAR TECHNOLOGY CONFERENCE, VTC2023-SPRING, 2023,
[3] Automatic Modulation Classification for CR Using Deep Learning
Surendra Solanki
Banalaxmi Brahma
Yadvendra Pratap Singh
SN Computer Science, 5 (8)
[4] Deep Learning based Automatic Signal Modulation Classification
Lu, Jingyang
Li, Yi
Chen, Genshe
Shen, Dan
Tian, Xin
Khanh Pham
SENSORS AND SYSTEMS FOR SPACE APPLICATIONS XII, 2019, 11017
[5] Automatic Modulation Classification in Deep Learning
Alnajjar, Khawla A.
Ghunaim, Sara
Ansari, Sam
2022 5TH INTERNATIONAL CONFERENCE ON COMMUNICATIONS, SIGNAL PROCESSING, AND THEIR APPLICATIONS (ICCSPA), 2022,
[6] Adversarial Transfer Learning for Deep Learning Based Automatic Modulation Classification
Bu, Ke
He, Yuan
Jing, Xiaojun
Han, Jindong
IEEE SIGNAL PROCESSING LETTERS, 2020, 27 : 880 - 884
[7] Modulation Classification of MQAM Signals Based on Gradient Color Constellation and Deep Learning
Huang, Gang
Li, Yue
Zhu, Qianqian
He, Chengguang
IWCMC 2021: 2021 17TH INTERNATIONAL WIRELESS COMMUNICATIONS & MOBILE COMPUTING CONFERENCE (IWCMC), 2021, : 1309 - 1313
[8] Automatic Modulation Classification of Cochannel Signals using Deep Learning
Sun, Jiajun
Wang, Guohua
Lin, Zhiping
Razul, Sirajudeen Gulam
Lai, Xiaoping
2018 IEEE 23RD INTERNATIONAL CONFERENCE ON DIGITAL SIGNAL PROCESSING (DSP), 2018,
[9] Imperceptible UAPs for Automatic Modulation Classification Based on Deep Learning
Xu, Dongwei
Li, Jiangpeng
Chen, Zhuangzhi
Xuan, Qi
Shen, Weiguo
Yang, Xiaoniu
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS, 2024, 71 (02) : 987 - 991
[10] Automatic Modulation Classification Using Deep Learning Based on Sparse Autoencoders With Nonnegativity Constraints
Ali, Afan
Fan Yangyu
IEEE SIGNAL PROCESSING LETTERS, 2017, 24 (11) : 1626 - 1630

← 1 2 3 4 5 →