Cost constrained spectrum sensing in cognitive radio networks

Gang Xiong, Shalinee Kishore, Aylin Yener

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    3 Citations (Scopus)

    Abstract

    This paper addresses optimal spectrum sensing in cognitive radio networks considering its system level cost that accounts for the local processing cost of sensing (sample collection and energy calculation at each secondary user) as well as the transmission cost (forwarding energy statistic from secondary users to fusion center). The optimization problem solves for the appropriate number of samples to be collected and amplifier gains at each secondary user to minimize the global error probability subject to a total cost constraint. In particular, closed-form expressions for optimal solutions are derived and a generalized water-filling algorithm is proposed when number of samples or amplifier gains are fixed and additional constraints are imposed. Furthermore, when jointly designing the number of samples and amplifier gains, optimal solution indicates that only one secondary user needs to be active, i.e., collecting samples for local energy calculation and transmitting energy statistic to fusion center.

    Original languageEnglish (US)
    Title of host publication2010 44th Annual Conference on Information Sciences and Systems, CISS 2010
    DOIs
    StatePublished - Jun 24 2010
    Event44th Annual Conference on Information Sciences and Systems, CISS 2010 - Princeton, NJ, United States
    Duration: Mar 17 2010Mar 19 2010

    Publication series

    Name2010 44th Annual Conference on Information Sciences and Systems, CISS 2010

    Other

    Other44th Annual Conference on Information Sciences and Systems, CISS 2010
    CountryUnited States
    CityPrinceton, NJ
    Period3/17/103/19/10

    Fingerprint

    Cognitive radio
    Costs
    Fusion reactions
    Statistics
    Processing
    Energy
    Water
    Fusion
    Optimal solution

    All Science Journal Classification (ASJC) codes

    • Information Systems
    • Information Systems and Management

    Cite this

    Xiong, G., Kishore, S., & Yener, A. (2010). Cost constrained spectrum sensing in cognitive radio networks. In 2010 44th Annual Conference on Information Sciences and Systems, CISS 2010 [5464978] (2010 44th Annual Conference on Information Sciences and Systems, CISS 2010). https://doi.org/10.1109/CISS.2010.5464978
    Xiong, Gang ; Kishore, Shalinee ; Yener, Aylin. / Cost constrained spectrum sensing in cognitive radio networks. 2010 44th Annual Conference on Information Sciences and Systems, CISS 2010. 2010. (2010 44th Annual Conference on Information Sciences and Systems, CISS 2010).
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    Xiong, G, Kishore, S & Yener, A 2010, Cost constrained spectrum sensing in cognitive radio networks. in 2010 44th Annual Conference on Information Sciences and Systems, CISS 2010., 5464978, 2010 44th Annual Conference on Information Sciences and Systems, CISS 2010, 44th Annual Conference on Information Sciences and Systems, CISS 2010, Princeton, NJ, United States, 3/17/10. https://doi.org/10.1109/CISS.2010.5464978

    Cost constrained spectrum sensing in cognitive radio networks. / Xiong, Gang; Kishore, Shalinee; Yener, Aylin.

    2010 44th Annual Conference on Information Sciences and Systems, CISS 2010. 2010. 5464978 (2010 44th Annual Conference on Information Sciences and Systems, CISS 2010).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

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    AB - This paper addresses optimal spectrum sensing in cognitive radio networks considering its system level cost that accounts for the local processing cost of sensing (sample collection and energy calculation at each secondary user) as well as the transmission cost (forwarding energy statistic from secondary users to fusion center). The optimization problem solves for the appropriate number of samples to be collected and amplifier gains at each secondary user to minimize the global error probability subject to a total cost constraint. In particular, closed-form expressions for optimal solutions are derived and a generalized water-filling algorithm is proposed when number of samples or amplifier gains are fixed and additional constraints are imposed. Furthermore, when jointly designing the number of samples and amplifier gains, optimal solution indicates that only one secondary user needs to be active, i.e., collecting samples for local energy calculation and transmitting energy statistic to fusion center.

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    Xiong G, Kishore S, Yener A. Cost constrained spectrum sensing in cognitive radio networks. In 2010 44th Annual Conference on Information Sciences and Systems, CISS 2010. 2010. 5464978. (2010 44th Annual Conference on Information Sciences and Systems, CISS 2010). https://doi.org/10.1109/CISS.2010.5464978