Short-time modulation classification of complex wireless communication signal based on deep neural network

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Citations (Scopus)

Abstract

Modulation classification of communication signal is one of the key technologies for realizing non-cooperative communication tasks, multi system communication interconnection and software radio. Therefore, when the decision process cannot wait for more data to increase certainty, how to effectively classify the modulation type in a short time is an unavoidable and challenging topic. In this paper, we make a performance comparison of traditional feature-based neural network and deep neural network (DNN) with complex digital modulation signal datasets. The results indicate that DNN has a stronger ability to extract classification features. Then we demonstrate two novel architectures based on DNN, which disentangle more meaning hidden features from the short-time signal and perform superiorly under limited signal length. Finally, we test the generalization ability of neural network models to signal-to-noise radio (SNR).

Original languageEnglish
Title of host publication2018 24th Asia-Pacific Conference on Communications, APCC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages520-524
Number of pages5
ISBN (Electronic)9781538669280
DOIs
Publication statusPublished - 2 Jul 2018
Event24th Asia-Pacific Conference on Communications, APCC 2018 - Ningbo, China
Duration: 12 Nov 201814 Nov 2018

Publication series

Name2018 24th Asia-Pacific Conference on Communications, APCC 2018

Conference

Conference24th Asia-Pacific Conference on Communications, APCC 2018
Country/TerritoryChina
CityNingbo
Period12/11/1814/11/18

Keywords

  • Modulation classification
  • machine learning
  • neural network
  • short-time
  • wireless communication

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Yin, R., Huang, J., & Fei, Z. (2018). Short-time modulation classification of complex wireless communication signal based on deep neural network. In 2018 24th Asia-Pacific Conference on Communications, APCC 2018 (pp. 520-524). Article 8633576 (2018 24th Asia-Pacific Conference on Communications, APCC 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/APCC.2018.8633576