Adaptive Decision-Making Scheme for Cognitive Radio Networks

Handle URI:
http://hdl.handle.net/10754/362476
Title:
Adaptive Decision-Making Scheme for Cognitive Radio Networks
Authors:
Alqerm, Ismail; Shihada, Basem ( 0000-0003-4434-4334 )
Abstract:
Radio resource management becomes an important aspect of the current wireless networks because of spectrum scarcity and applications heterogeneity. Cognitive radio is a potential candidate for resource management because of its capability to satisfy the growing wireless demand and improve network efficiency. Decision-making is the main function of the radio resources management process as it determines the radio parameters that control the use of these resources. In this paper, we propose an adaptive decision-making scheme (ADMS) for radio resources management of different types of network applications including: power consuming, emergency, multimedia, and spectrum sharing. ADMS exploits genetic algorithm (GA) as an optimization tool for decision-making. It consists of the several objective functions for the decision-making process such as minimizing power consumption, packet error rate (PER), delay, and interference. On the other hand, maximizing throughput and spectral efficiency. Simulation results and test bed evaluation demonstrate ADMS functionality and efficiency.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
2014 IEEE 28th International Conference on Advanced Information Networking and Applications
Conference/Event name:
28th IEEE International Conference on Advanced Information Networking and Applications, IEEE AINA 2014
Issue Date:
May-2014
DOI:
10.1109/AINA.2014.41
Type:
Conference Paper
Additional Links:
http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6838682
Appears in Collections:
Conference Papers; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorAlqerm, Ismailen
dc.contributor.authorShihada, Basemen
dc.date.accessioned2015-04-09T06:34:11Zen
dc.date.available2015-04-09T06:34:11Zen
dc.date.issued2014-05en
dc.identifier.doi10.1109/AINA.2014.41en
dc.identifier.urihttp://hdl.handle.net/10754/362476en
dc.description.abstractRadio resource management becomes an important aspect of the current wireless networks because of spectrum scarcity and applications heterogeneity. Cognitive radio is a potential candidate for resource management because of its capability to satisfy the growing wireless demand and improve network efficiency. Decision-making is the main function of the radio resources management process as it determines the radio parameters that control the use of these resources. In this paper, we propose an adaptive decision-making scheme (ADMS) for radio resources management of different types of network applications including: power consuming, emergency, multimedia, and spectrum sharing. ADMS exploits genetic algorithm (GA) as an optimization tool for decision-making. It consists of the several objective functions for the decision-making process such as minimizing power consumption, packet error rate (PER), delay, and interference. On the other hand, maximizing throughput and spectral efficiency. Simulation results and test bed evaluation demonstrate ADMS functionality and efficiency.en
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.relation.urlhttp://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6838682en
dc.rights(c) 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.en
dc.titleAdaptive Decision-Making Scheme for Cognitive Radio Networksen
dc.typeConference Paperen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.identifier.journal2014 IEEE 28th International Conference on Advanced Information Networking and Applicationsen
dc.conference.date13 May 2014 through 16 May 2014en
dc.conference.name28th IEEE International Conference on Advanced Information Networking and Applications, IEEE AINA 2014en
dc.conference.locationVictoria, BCen
dc.eprint.versionPost-printen
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)en
kaust.authorShihada, Basemen
kaust.authorAlqerm, Ismailen
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