Various Modulation Types Classification on the Air by Convolutional Neural Network-Reference-Cited by-同舟云学术

Various Modulation Types Classification on the Air by Convolutional Neural Network

Published:2023-12-21 Issue: Volume:2016 Page:779-786
ISSN:
Container-title:Proceedings of the 7th International Conference on Future Networks and Distributed Systems
language:
Short-container-title:

Author:

Hammadi Yousif I¹^ORCID,Alsaeedi Mokhalad Abdulameer Kadhim²^ORCID,Mahmood Omar Abdulkareem²^ORCID,Sameen Aws Zuhair³^ORCID,Muthanna Mohammed Saleh Ali⁴^ORCID,Aziz Ahmed⁵^ORCID,Muthanna Ammar⁶^ORCID

Affiliation:

1. Dep. of Medical Instruments Engineering Techniques, Bilad Alrafidain University College, Iraq

2. Department of Communications Engineering, University of Diyala, Iraq

3. Department of Medical Instrumentation Engineering Techniques, Al-Farahidi University, Iraq

4. Institute of Computer Technologies and Information Security, Southern Federal University, Russia

5. Department of computer science, Benha university, Egypt and International Business Management Department, Tashkent State University of Economics, Uzbekistan

6. Department of Telecommunication Networks and Data Transmission, The Bonch Bruevich Saint Petersburg State University of Telecommunications, Russia and Department of Applied Probability and Informatics, Peoples Friendship University of Russia, Russia

Funder

Ministry of Science and High Education of the Russian Federation

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3644713.3644855

Reference27 articles.

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2. E. H. Salman, M. A. Taher, Y. I. Hammadi, O. A. Mahmood, A. Muthanna, and A. Koucheryavy.: An Anomaly Intrusion Detection for High-Density Internet of Things Wireless Communication Network Based Deep Learning Algorithms. Sensors, 23(1), 206 (2023) [Online]. Available: https://www.mdpi.com/1424-8220/23/1/206.

3. Survey of automatic modulation classification techniques: classical approaches and new trends

4. O. A. Dobre and F. Hameed.: Likelihood-Based Algorithms for Linear Digital Modulation Classification in Fading Channels. In 2006 Canadian Conference on Electrical and Computer Engineering, pp. 1347–1350. IEEE, Ottawa, ON, Canada (2006)

5. ALWAN, Mohammed Hasan, A Novel Technique for Creating Optical Multi-carrier Generation Using Nested Electro-Absorption Modulators. In: International Conference on Distributed Computer and Communication Networks. Cham: Springer Nature Switzerland, 2022. p. 17-28.‏