Stammdaten

Titel: A Channel Allocation Algorithm for Cognitive Radio Users Based on Channel State Predictors
Untertitel:
Kurzfassung:

Cognitive radio networks can efficiently manage the radio spectrum by utilizing the spectrum holes for secondary users in licensed frequency bands. The energy that is used to detect spectrum holes can be reduced considerably by predicting them. However, collisions can occur either between a primary user and secondary users or among the secondary users themselves. This paper introduces a centralized channel allocation algorithm (CCAA) in a scenario with multiple secondary users to control primary and secondary collisions. The proposed allocation algorithm, which uses a channel state predictor (CSP), provides good performance with fairness among the secondary users while they have minimal interference with the primary user. The simulation results show that the probability of a wrong prediction of an idle channel state in a multi-channel system is less than 0.9%. The channel state prediction saves the sensing energy by 73%, and the utilization of the spectrum can be improved by more than 77%.

Schlagworte: Cognitive radio, Neural networks, Prediction, Idle channel
Publikationstyp: Beitrag in Sammelwerk (Autorenschaft)
Erscheinungsdatum: 17.09.2021 (Online)
Erschienen in: ICICT 21' Proceedings of Sixth International Congress on Information and Communication Technology
ICICT 21' Proceedings of Sixth International Congress on Information and Communication Technology
zur Publikation
 ( Springer; X. Yang, S. Sherratt, N. Dey, A. Joshi )
Titel der Serie: Lecture Notes in Networks and Systems
Bandnummer: 235
Erstveröffentlichung: Ja
Version: -
Seite: S. 711 - 719

Versionen

Keine Version vorhanden
Erscheinungsdatum: 17.09.2021
ISBN (e-book):
  • 978-981-16-2379-0
  • 978-981-16-2380-6
eISSN: 2367-3389
DOI: http://dx.doi.org/10.1007/978-981-16-2380-6_62
Homepage: https://link.springer.com/chapter/10.1007/978-981-16-2380-6_62
Open Access
  • Online verfügbar (nicht Open Access)

Zuordnung

Organisation Adresse
Fakultät für Technische Wissenschaften
 
Institut für Informationstechnologie
Universitaetsstr. 65-67
9020 Klagenfurt am Wörthersee
Österreich
   martina.steinbacher@aau.at
http://itec.aau.at/
zur Organisation
Universitaetsstr. 65-67
AT - 9020  Klagenfurt am Wörthersee

Kategorisierung

Sachgebiete
  • 1020 - Informatik
Forschungscluster Kein Forschungscluster ausgewählt
Peer Reviewed
  • Ja
Publikationsfokus
  • Science to Science (Qualitätsindikator: III)
Klassifikationsraster der zugeordneten Organisationseinheiten:
Arbeitsgruppen
  • Multimedia Communication

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Organisation Adresse
Université du Québec
475, rue du Parvis
G1K 9H7 Québec
Kanada
475, rue du Parvis
CA - G1K 9H7  Québec

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