Digital modulation classification based on BAT swarm optimization and random forest
Joint Authors
Hasan, Taha Muhammad
Sultan, Batul Abd al-Hadi
Hamid, Hadi Adhab
Source
Journal of Kufa for Mathematics and Computer
Issue
Vol. 7, Issue 1 (31 Mar. 2020), pp.26-30, 5 p.
Publisher
University of Kufa Faculty of Mathematics and Computers Science
Publication Date
2020-03-31
Country of Publication
Iraq
No. of Pages
5
Main Subjects
Information Technology and Computer Science
Abstract EN
The applications of digitally modulated signals are still in progress and expansion.
automatic modulation identification (AMI) is important to classify the digitally modulated signals ..to get better results of the system suggested optimization the features to discard weak or irrelevant features in the system and keep only strong relevant features .in this work, present hybrid intelligent system for the recognition related to the digitally modulated signals where used .
the proposed (AMI) had been built to classify ten most popular schemes of digitally modulated signals, namely (2ASK, , 2PSK, 4PSK, 8PSK, 8QAM,16QAM ,32QAM, 64 QAM, 128QAM, and 256QAM), with the signal to noise ratio ranging from (-2 to 13) dB.
High-order cumulants (HOCs) as well as high-order moments (HOMs) were utilized.
.in this thesis used , bat swarm optimization (BA).the random forest ( RF) classifier was introduced for the first time in this work.
Simulation results of the System proposed , under additive white gaussian noise channel, show that .While algorithm ( BA Swarm Optimization ) for the modulated signals we obtained a classification accuracy of around 92% for the SNR between (-2....12 ) dB.
American Psychological Association (APA)
Sultan, Batul Abd al-Hadi& Hasan, Taha Muhammad& Hamid, Hadi Adhab. 2020. Digital modulation classification based on BAT swarm optimization and random forest. Journal of Kufa for Mathematics and Computer،Vol. 7, no. 1, pp.26-30.
https://search.emarefa.net/detail/BIM-1495403
Modern Language Association (MLA)
Sultan, Batul Abd al-Hadi…[et al.]. Digital modulation classification based on BAT swarm optimization and random forest. Journal of Kufa for Mathematics and Computer Vol. 7, no. 1 (Mar. 2020), pp.26-30.
https://search.emarefa.net/detail/BIM-1495403
American Medical Association (AMA)
Sultan, Batul Abd al-Hadi& Hasan, Taha Muhammad& Hamid, Hadi Adhab. Digital modulation classification based on BAT swarm optimization and random forest. Journal of Kufa for Mathematics and Computer. 2020. Vol. 7, no. 1, pp.26-30.
https://search.emarefa.net/detail/BIM-1495403
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 29-30
Record ID
BIM-1495403