Melola Discovery

← Melola Discovery

Open access Jurnal SINTA 1

New Approaches in Cognitive Radios using Evolutionary Algorithms

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 8 No. 3 (2018)

DOI
10.11591/ijece.v8i3.pp1636-1646
ISSN
2088-8708, 2088-8708
Published
2018-06-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-nc/4.0

Abstract

Cognitive radio has claimed a promising technology to exploit the spectrum in an ad hoc network. Due many techniques have become a topic of discussion on cognitive radios, the aim of this paper was developed a contemporary survey of evolutionary algorithms in Cognitive Radio. According to the art state, this work had been collected the essential contributions of cognitive radios with the particularity of base they research in evolutionary algorithms. The main idea was classified the evolutionary algorithms and showed their fundamental approaches. Moreover, this research will be exposed some of the current issues in cognitive radios and how the evolutionary algorithms will have been contributed. Therefore, current technologies have matters presented in optimization, learning, and classification over cognitive radios where evolutionary algorithms can be presented big approaches. With a more comprehensive and systematic understanding of evolutionary algorithms in cognitive radios, more research in this direction may be motivated and refined.

Collaboration network of the authors

10 authors · 15 co-authorship links

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Universidad Distrital Francisco José de Caldas
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Diego GiralUniversidad Distrital Francisco José de Caldas3
Fredy MartinezUniversidad Distrital Francisco José de Caldas2
Hans López-ChávezUniversidad Distrital Francisco José de Caldas2
Julian MartinezAffiliation unknown1
Luis PedrazaAffiliation unknown1
Fernando MartínezUniversidad Distrital Francisco José de Caldas1
Ángel FarfánUniversidad Distrital Francisco José de Caldas1
Tania VacaUniversidad Distrital Francisco José de Caldas1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>New Approaches in Cognitive Radios using Evolutionary Algorithms</dc:title><dc:creator>Tuberquia, Miguel</dc:creator><dc:creator>Hernandez, Cesar</dc:creator><dc:description>&lt;jats:p&gt;Cognitive radio has claimed a promising technology to exploit the spectrum in an ad hoc network. Due many techniques have become a topic of discussion on cognitive radios, the aim of this paper was developed a contemporary survey of evolutionary algorithms in Cognitive Radio. According to the art state, this work had been collected the essential contributions of cognitive radios with the particularity of base they research in evolutionary algorithms. The main idea was classified the evolutionary algorithms and showed their fundamental approaches. Moreover, this research will be exposed some of the current issues in cognitive radios and how the evolutionary algorithms will have been contributed. Therefore, current technologies have matters presented in optimization, learning, and classification over cognitive radios where evolutionary algorithms can be presented big approaches. With a more comprehensive and systematic understanding of evolutionary algorithms in cognitive radios, more research in this direction may be motivated and refined.&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2018-06-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v8i3.pp1636-1646</dc:identifier><dc:identifier>10.11591/ijece.v8i3.pp1636-1646</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 8 No 3 (2018); 1636</dc:source><dc:source>2088-8708</dc:source><dc:source>2088-8708</dc:source><dc:relation>http://ijece.iaescore.com/index.php/IJECE/article/viewFile/9666/8704</dc:relation><dc:rights>http://creativecommons.org/licenses/by-nc/4.0</dc:rights></oai_dc:dc>