Click to open the HelpDesk interface
AECE - Front page banner



JCR Impact Factor: 1.102
JCR 5-Year IF: 0.734
Issues per year: 4
Current issue: Aug 2020
Next issue: Nov 2020
Avg review time: 96 days


Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


2,685,113 unique visits
Since November 1, 2009

No robots online now


SCImago Journal & Country Rank


Anycast DNS Hosting

 Volume 20 (2020)
     »   Issue 3 / 2020
     »   Issue 2 / 2020
     »   Issue 1 / 2020
 Volume 19 (2019)
     »   Issue 4 / 2019
     »   Issue 3 / 2019
     »   Issue 2 / 2019
     »   Issue 1 / 2019
 Volume 18 (2018)
     »   Issue 4 / 2018
     »   Issue 3 / 2018
     »   Issue 2 / 2018
     »   Issue 1 / 2018
 Volume 17 (2017)
     »   Issue 4 / 2017
     »   Issue 3 / 2017
     »   Issue 2 / 2017
     »   Issue 1 / 2017
 Volume 16 (2016)
     »   Issue 4 / 2016
     »   Issue 3 / 2016
     »   Issue 2 / 2016
     »   Issue 1 / 2016
  View all issues  


Clarivate Analytics published the InCites Journal Citations Report for 2019. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 1.102 (1.023 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.734.

Starting on the 15th of June 2020 we wiil introduce a new policy for reviewers. Reviewers who provide timely and substantial comments will receive a discount voucher entitling them to an APC reduction. Vouchers (worth of 25 EUR or 50 EUR, depending on the review quality) will be assigned to reviewers after the final decision of the reviewed paper is given. Vouchers issued to specific individuals are not transferable.

Starting on the 15th of December 2019 all paper authors are required to enter their SCOPUS IDs. You may use the free SCOPUS ID lookup form to find yours in case you don't remember it.

Clarivate Analytics published the InCites Journal Citations Report for 2018. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.650, and the JCR 5-Year Impact Factor is 0.639.

Starting today, the minimum number a pages for a paper is 8, so all submitted papers should have 8, 10 or 12 pages. No exceptions will be accepted.

Read More »


  4/2019 - 8

Research on Influencing Factors of Digital Signal Modulation Recognition

WANG, J. See more information about WANG, J. on SCOPUS See more information about WANG, J. on IEEExplore See more information about WANG, J. on Web of Science, DU, H. See more information about DU, H. on SCOPUS See more information about DU, H. on SCOPUS See more information about DU, H. on Web of Science
Click to see author's profile in See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (550 KB) | Citation | Downloads: 182 | Views: 387

Author keywords
pattern recognition, digital modulation, higher order statistics, multiple signal classification, machine learning

References keywords
modulation(21), recognition(13), order(12), communications(12), signal(9), digital(8), cumulants(8), classification(8), automatic(7), signals(6)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2019-11-30
Volume 19, Issue 4, Year 2019, On page(s): 65 - 72
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2019.04008
Web of Science Accession Number: 000500274700007
SCOPUS ID: 85077254689

Quick view
Full text preview
In the real environment, modulation recognition has low classification recognition rate under low SNR and is affected by many factors such as symbol rate, frequency offset and adjacent channel crosstalk. Based on the combination of high-order cumulants and instantaneous features, this paper firstly analyzes the performance of modulation signal recognition in Gaussian environment. Then through the experimental verification, symbol rate, frequency offset, adjacent channel crosstalk has an impact on the accuracy of modulation recognition. The experimental results show that the ratio of symbol rate and sampling rate has a significant impact on the recognition results, while frequency offset and adjacent channel crosstalk have little impact on the recognition rate.

References | Cited By  «-- Click to see who has cited this paper

[1] T. Liu, Y. Guan, Y. Lin, "Research on modulation recognition with ensemble learning," EURASIP Journal on Wireless Communications and Networking, vol. 179, no. 1, 2017.
[CrossRef] [Web of Science Times Cited 27] [SCOPUS Times Cited 28]

[2] L. Zhang, "Research on modulation recognition algorithm based on high-order cumulant," Journal of Information Engineering University, vol. 18, no. 4, pp. 403-408, 2017.

[3] J. J. Guo, H. D. Yin, L. Jiang, "Recognition of digital modulation signals via high-order cumulants," Communications Technology, vol. 47, no. 11, pp. 1255-1260, 2014.

[4] A. Swami and B. Sadler, "Modulation classification via hierarchical agglomerative cluster analysis," In First IEEE Signal Processing Workshop on Signal Processing Advances in Wireless Communications, pp. 141-144, 1997.
[CrossRef] [Web of Science Times Cited 12]

[5] C. M. Spooner, "On the utility of sixth-order cyclic cumulants for RF signal classification," In Conference Record of Thirty-Fifth Asilomar Conference on Signals, Systems and Computers, vol. 1, pp. 890-897, 2001.
[CrossRef] [Web of Science Times Cited 65] [SCOPUS Times Cited 89]

[6] O. A. Dobre, Y. Barness, and W. Su, "Higher-order cyclic cumulants for high order modulation classification," In IEEE Military Communications Conference, vol. 1, pp. 112-117, 2003.

[7] H. Wu, M. Saquib, and Z. Yun, "Novel Automatic Modulation Classification Using Cumulant Features for Communications via Multipath Channels," IEEE Transactions on Wireless Communications, vol. 7, no. 8, pp. 3098-3105, 2008.
[CrossRef] [Web of Science Times Cited 158] [SCOPUS Times Cited 195]

[8] L. Liu and J. Xu, "A Novel Modulation Classification Method Based on High Order Cumulants," In 2006 International Conference on Wireless Communications, Networking and Mobile Computing, pp. 1-5, 2006.
[CrossRef] [SCOPUS Times Cited 31]

[9] Y. Q. Zhang , "Digital Signal Modulation Recognition Based on Higher Order Cumulants," Information & Communications, vol. 2, pp. 27-30, 2016.

[10] Li Y., Guo X. G., Zhao X., "Study on Modulation Recognition Based on Higher-Order Cumulants," Journal of Southwest University of Science and Technology (Natural Science Edition), vol. 33, no. 3, pp. 64-68, 2018.

[11] Hu X., Liu H. L., Zhang J. C., "Algorithm of Modulation Identification Based on Higher Order Cumulant and Instantaneous Characteristics," World Science and Technology Research and Development, vol. 33, no. 6, pp. 1002-1005, 2011.

[12] Yuan L.F., Ning S.G., He Y.G, Lyu M., Lu J., "Modulation recognition method based on high-order cumulant feature learning," Systems Engineering and Electronics, vol. 41, no. 9, pp. 2122-2131.
[CrossRef] [SCOPUS Times Cited 1]

[13] W. Juanping, H. Yingzheng, Z. Jinmei, and W. Huakui, "Automatic Modulation Recognition of Digital Communication Signals," presented at the international conference on pervasive computing, 2010, pp. 590-593.
[CrossRef] [SCOPUS Times Cited 7]

[14] W. Xie, S. Hu, C. Yu, P. Zhu, X. Peng, and J. Ouyang, "Deep Learning in Digital Modulation Recognition Using High Order Cumulants," IEEE Access, vol. 7, pp. 63760-63766, 2019.
[CrossRef] [Web of Science Times Cited 9] [SCOPUS Times Cited 14]

[15] E. E. Azzouz and A. K. Nandi, "Automatic identification of digital modulation types," Signal Processing, vol. 47, no. 1, pp. 55-69, 1995.
[CrossRef] [Web of Science Times Cited 138] [SCOPUS Times Cited 187]

[16] A. K. Nandi and E. E. Azzouz, "Algorithms for automatic modulation recognition of communication signals," IEEE Transactions on Communications, vol. 46, no. 4, pp. 431-436, 1998.
[CrossRef] [Web of Science Times Cited 303] [SCOPUS Times Cited 444]

[17] G. P. Zhang, "Neural networks for classification: a survey," systems man and cybernetics, vol. 30, no. 4, pp. 451-462, 2000.
[CrossRef] [Web of Science Times Cited 816] [SCOPUS Times Cited 1138]

[18] A. E. Shermeh and R. Ghazalian, "Recognition of communication signal types using genetic algorithm and support vector machines based on the higher order statistics," Digital Signal Processing, vol. 20, no. 6, pp. 1748-1757, 2010.
[CrossRef] [Web of Science Times Cited 17] [SCOPUS Times Cited 20]

[19] Flohberger, M., Gappmair, W., & Koudelka, O., "Modulation classifier for signals used in satellite communications," In 2010 5th Advanced Satellite Multimedia Systems Conference and the 11th Signal Processing for Space Communications Workshop, pp. 198-202, 2010.
[CrossRef] [Web of Science Times Cited 3] [SCOPUS Times Cited 13]

[20] A. Swami and B. M. Sadler, "Hierarchical digital modulation classification using cumulants," IEEE Transactions on Communications, vol. 48, no. 3, pp. 416-429, 2000.
[CrossRef] [Web of Science Times Cited 558] [SCOPUS Times Cited 720]

[21] A. K. Nandi and E. E. Azzouz, "Automatic analogue modulation recognition," Signal Processing, vol. 46, no. 2, pp. 211-222, 1995.
[CrossRef] [Web of Science Times Cited 76] [SCOPUS Times Cited 114]

[22] H. U. Youqiang, J. Liu, and X. Tan, "Digital modulation recognition based on instantaneous information," The Journal of China Universities of Posts and Telecommunications, vol. 17, no. 3, pp. 52-90, 2010.
[CrossRef] [SCOPUS Times Cited 15]

[23] L. I. Qiuna, "Modulation Classification Method of MQAM Signals Based on Amplitude Statistical Moment," Computer Simulation, 2009.

[24] Y. Ettefagh, M. H. Moghaddam, and S. Eghbalian, "An adaptive neural network approach for automatic modulation recognition," presented at the conference on information sciences and systems, 2017, pp. 1-5.
[CrossRef] [SCOPUS Times Cited 4]

[25] S. K. Murthy, "Automatic Construction of Decision Trees from Data: A Multi-Disciplinary Survey," Data Mining and Knowledge Discovery, vol. 2, no. 4, pp. 345-389, 1998.
[CrossRef] [Web of Science Times Cited 467] [SCOPUS Times Cited 606]

[26] Maimon, O., Rokach, L., "Decision trees," Data mining and knowledge discovery handbook. Springer, Boston, MA, 2005, pp. 165-192.
[CrossRef] [Web of Science Times Cited 241]

References Weight

Web of Science® Citations for all references: 2,890 TCR
SCOPUS® Citations for all references: 3,626 TCR

Web of Science® Average Citations per reference: 107 ACR
SCOPUS® Average Citations per reference: 134 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2020-10-22 07:52 in 166 seconds.

Note1: Web of Science® is a registered trademark of Clarivate Analytics.
Note2: SCOPUS® is a registered trademark of Elsevier B.V.
Disclaimer: All queries to the respective databases were made by using the DOI record of every reference (where available). Due to technical problems beyond our control, the information is not always accurate. Please use the CrossRef link to visit the respective publisher site.

Copyright ©2001-2020
Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania

All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.

Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.

Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.

Website loading speed and performance optimization powered by: