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An Evolutionary Cognitive Radio Adaptation Engine Architecture Inspired from Cognitive Sciences

by Ramy A. Fathy, Abdelhalim Zekry, Ahmed A. Abdel Hafez
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 70 - Number 25
Year of Publication: 2013
Authors: Ramy A. Fathy, Abdelhalim Zekry, Ahmed A. Abdel Hafez
10.5120/12226-8510

Ramy A. Fathy, Abdelhalim Zekry, Ahmed A. Abdel Hafez . An Evolutionary Cognitive Radio Adaptation Engine Architecture Inspired from Cognitive Sciences. International Journal of Computer Applications. 70, 25 ( May 2013), 37-45. DOI=10.5120/12226-8510

@article{ 10.5120/12226-8510,
author = { Ramy A. Fathy, Abdelhalim Zekry, Ahmed A. Abdel Hafez },
title = { An Evolutionary Cognitive Radio Adaptation Engine Architecture Inspired from Cognitive Sciences },
journal = { International Journal of Computer Applications },
issue_date = { May 2013 },
volume = { 70 },
number = { 25 },
month = { May },
year = { 2013 },
issn = { 0975-8887 },
pages = { 37-45 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume70/number25/12226-8510/ },
doi = { 10.5120/12226-8510 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:33:50.814076+05:30
%A Ramy A. Fathy
%A Abdelhalim Zekry
%A Ahmed A. Abdel Hafez
%T An Evolutionary Cognitive Radio Adaptation Engine Architecture Inspired from Cognitive Sciences
%J International Journal of Computer Applications
%@ 0975-8887
%V 70
%N 25
%P 37-45
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Cognitive Radio (CR) is the future of radio systems giving authorities and end users unprecedented capabilities, and completely new services expectations. This paper aims at introducing an evolutionary novel Cognitive Radio adaptation engine architecture inspired from theories developed in cognitive sciences. Adaptation is a fundamental feature of CR necessary for many applications and use cases such as dynamic spectrum access, and emergency and disaster relief communication systems. The proposed architecture employs meta-heuristic techniques to dynamically and autonomously self-adapt to external varying stimuli, in order to reach some objectives. The implemented architecture is shown to be suitable for applications of emergency and disaster relief communication systems.

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Index Terms

Computer Science
Information Sciences

Keywords

Adaptation Cycle Adaptation Engine Architecture Cognition Cycle Cognitive Sciences

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