Publication detail

Noise Robust Automatic Digital Modulation Recognition Based on Gaussian Mixture Models

KUBÁNKOVÁ, A. ATASSI, H. KUBÁNEK, D.

Original Title

Noise Robust Automatic Digital Modulation Recognition Based on Gaussian Mixture Models

English Title

Noise Robust Automatic Digital Modulation Recognition Based on Gaussian Mixture Models

Type

conference paper

Language

en

Original Abstract

The paper describes a method for the classification of digital modulations. The method uses features computed from parameters of recognized signal such as instantaneous amplitude, instantaneous phase, and spectrum symmetry. A classifier based on Gaussian mixture models was used to analyze the features and classify the modulations. ASK, FSK, MSK, BPSK, QPSK, and QAM-16 were chosen for the classification as the best-known digital modulations used in modern communication technologies. The effectivity of the method designed was tested using signals corrupted by white Gaussian noise.

English abstract

The paper describes a method for the classification of digital modulations. The method uses features computed from parameters of recognized signal such as instantaneous amplitude, instantaneous phase, and spectrum symmetry. A classifier based on Gaussian mixture models was used to analyze the features and classify the modulations. ASK, FSK, MSK, BPSK, QPSK, and QAM-16 were chosen for the classification as the best-known digital modulations used in modern communication technologies. The effectivity of the method designed was tested using signals corrupted by white Gaussian noise.

Keywords

Classification of modulations, recognition, features, Gaussian mixture models

RIV year

2011

Released

02.02.2011

Publisher

VUT v Brně

Location

Brno, Czech Republic

ISBN

978-80-214-4231-3

Book

Proceedings of the 6th International Conference on Teleinformatics - ICT 2011 (id 18951)

Pages from

220

Pages to

226

Pages count

7

BibTex


@inproceedings{BUT74186,
  author="Anna {Kubánková} and Hicham {Atassi} and David {Kubánek}",
  title="Noise Robust Automatic Digital Modulation Recognition Based on Gaussian Mixture Models",
  annote="The paper describes a method for the classification of digital modulations. The method uses features computed from parameters of recognized signal such as instantaneous amplitude, instantaneous phase, and spectrum symmetry. A classifier based on Gaussian mixture models was used to analyze the features and classify the modulations. ASK, FSK, MSK, BPSK, QPSK, and QAM-16 were chosen for the classification as the best-known digital modulations used in modern communication technologies. The effectivity of the method designed was tested using signals corrupted by white Gaussian noise.",
  address="VUT v Brně",
  booktitle="Proceedings of the 6th International Conference on Teleinformatics - ICT 2011 (id 18951)",
  chapter="74186",
  howpublished="electronic, physical medium",
  institution="VUT v Brně",
  year="2011",
  month="february",
  pages="220--226",
  publisher="VUT v Brně",
  type="conference paper"
}