Performance improvement with predictive channel selection for cognitive radios

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

    75 Citations (Scopus)

    Abstract

    Prediction of future availability times of different channels based on history information helps a cognitive radio (CR) to select the best channels for control and data transmission. Different prediction rules apply to periodic and stochastic ON-OFF patterns. A CR can learn the patterns in different channels over time. We propose a simple classification and learning method to detect the pattern type and to gather the needed information for intelligent channel selection. Matlab simulations show that the proposed method outperforms opportunistic random channel selection both with stochastic and periodic channel patterns. The amount of channel switches needed over time reduces up to 55%, which reduces also the delay and increases the throughput.
    Original languageEnglish
    Title of host publication2008 First International Workshop on Cognitive Radio and Advanced Spectrum Management
    PublisherIEEE Institute of Electrical and Electronic Engineers
    Pages23-27
    ISBN (Electronic)978-1-4244-2140-4
    ISBN (Print)978-1-4244-2139-8
    DOIs
    Publication statusPublished - 2008
    MoE publication typeA4 Article in a conference publication
    EventFirst IEEE International Workshop on Cognitive Radio and Advanced Spectrum Management, IEEE CogART'08 - Aalborg, Denmark
    Duration: 14 Feb 200814 Feb 2008
    Conference number: 1

    Workshop

    WorkshopFirst IEEE International Workshop on Cognitive Radio and Advanced Spectrum Management, IEEE CogART'08
    Abbreviated titleIEEE CogART'08
    Country/TerritoryDenmark
    CityAalborg
    Period14/02/0814/02/08

    Keywords

    • prediction
    • learning
    • dynamic frequency management
    • cognitive radio
    • chromium
    • learning systems
    • stochastic processes
    • switches
    • history

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