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Cited by 703Wireless Signal Modulation ClassificationCognitive Radio Networks and Spectrum SensingAdvanced Signal Processing Techniques

The DOI matches its Crossref record.

Algorithms for automatic modulation recognition of communication signals

Nandi, A.K., Azzouz, E.E.·1998·IEEE Transactions on Communications
DOI 10.1109/26.664294
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Abstract

This paper introduces two algorithms for analog and digital modulations recognition. The first algorithm utilizes the decision-theoretic approach in which a set of decision criteria for identifying different types of modulations is developed. In the second algorithm the artificial neural network (ANN) is used as a new approach for the modulation recognition process. Computer simulations of different types of band-limited analog and digitally modulated signals corrupted by band-limited Gaussian noise sequences have been carried out to measure the performance of the developed algorithms. In the decision-theoretic algorithm it is found that the overall success rate is over 94% at the signal-to-noise ratio (SNR) of 15 dB, while in the ANN algorithm the overall success rate is over 96% at the SNR of 15 dB.

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Research works printed but not linked: 15

  1. 10.1016/0165-1684(95)00099-2 · DOI
  2. 10.1109/26.380199 · DOI
  3. 10.1016/0165-1684(84)90063-X · DOI
  4. 10.1016/0165-1684(85)90144-6 · DOI
  5. 10.1016/0165-1684(91)90012-8 · DOI
  6. 10.1007/978-1-4757-2469-1 · DOI
  7. nagy, 1994, analysis of a method for classification of analogue modulated radio signals, Proc EUSIPCO 94, ii, 1015
  8. 10.1016/0165-1684(89)90093-5 · DOI
  9. 10.1016/0165-1684(95)00083-P · DOI
  10. 10.1016/0165-1684(94)00128-M · DOI
  11. 10.1049/ip-f-2.1990.0066 · DOI
  12. 10.1109/26.58753 · DOI
  13. fabrizi, 1986, receiver recognition of analogue modulation types, IERE Conf Radio Receiver and Associated Systems, 135
  14. callaghan, 1985, sampling and algorithms aid modulation recognition, Microwaves RF, 24, 117–119, 121
  15. 10.1109/26.141456 · DOI

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Metadata

Authors
Nandi, A. K., & Azzouz, E. E.
Affiliations
University of Strathclyde (GB)
ORCID
Nandi, A.K.
Venue
IEEE Transactions on Communications
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
1998-04
Volume
46
Issue
4
Pages
431-436
ISSN
0090-6778 (ISSN-L)
DOI
10.1109/26.664294
OpenAlex
W2130014182
Cited by
703
References
0
Citations by year
2026: 20 · 2025: 22 · 2024: 44 · 2023: 31 · 2022: 41 · 2021: 48 · 2020: 33 · 2019: 39 · 2018: 26 · 2017: 19 · 2016: 23 · 2015: 25 · 2014: 23 · 2013: 31 · 2012: 33
FWCI
1.25
Type
journal article
Language
en
Open access
closed
Licence
ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html (vor)
Locations
IEEE Transactions on Communications (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Wireless Signal Modulation Classification
  • Physical Sciences › Computer Science › Computer Networks and Communications › Cognitive Radio Networks and Spectrum Sensing
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Signal Processing Techniques
Keywords
automatic modulation classification, digital modulation, analog modulation, artificial neural networks, band-limited signals, Gaussian noise, signal-to-noise ratio, modulation type identification

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CoChat. (2026). Citation check: Algorithms for automatic modulation recognition of communication signals. https://app.cochat.ai/papers/10.1109/26.664294
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Nandi, A. K., & Azzouz, E. E. (1998). Algorithms for automatic modulation recognition of communication signals. IEEE Transactions on Communications. https://doi.org/10.1109/26.664294