Detailed Information
Cited 0 time in 
Cited 0 time in 
Cited 0 time in
Metadata Downloads
Classification of Single- and Multi-carrier Signals Using CNN Based Deep Learning
- Authors
- An, Sungbae; Jang, Mingyu; Yoon, Dongweon
- Issue Date
- Jan-2022
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Keywords
- classification; convolutional neural network; deep learning; orthogonal frequency division multiplexing; single-carrier
- Citation
- Proceedings of 2021 7th IEEE International Conference on Network Intelligence and Digital Content, IC-NIDC 2021, pp.196 - 199
- Indexed
- SCOPUS
- Journal Title
- Proceedings of 2021 7th IEEE International Conference on Network Intelligence and Digital Content, IC-NIDC 2021
- Start Page
- 196
- End Page
- 199
- ISSN
- 0000-0000
- Abstract
- In a non-cooperative context, to recover data from the received signal, the receiver must estimate the communication parameters used in the transmitter. In this paper, we propose an algorithm for classifying single-carrier and multi-carrier signals by using convolutional neural network based deep learning and analyze classification performance. Simulation results show that the proposed algorithm outperforms the conventional methods in an additive white Gaussian noise channel and Rician fading channel. © 2021 IEEE.
- Files in This Item
- Go to Link
- Appears in
Collections - 서울 공과대학 > 서울 융합전자공학부 > 1. Journal Articles
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
Related Researcher
- Yoon, Dongweon
- COLLEGE OF ENGINEERING (SCHOOL OF ELECTRONIC ENGINEERING)