On low complexity cooperative spectrum sensing for cognitive networks

Gang Xiong, Shalinee Kishore, Aylin Yener

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

    8 Citations (Scopus)

    Abstract

    This paper presents a practical system design approach for cooperative spectrum sensing in cognitive sensor networks. An optimization problem is formulated, where the objective is to choose appropriate number of samples used in local energy calculation and linear combination weights for a global fusion center that together maximize global spectrum detection probability. Depending on the local information available to the fusion center and secondary users, practical system design is proposed in high fusion signal to noise ratio (SNR) regime, which has minimal implementation complexity and negligible performance loss, thus provides an efficient system design alternative in practice. Simulation results are presented to verify the analytical results.

    Original languageEnglish (US)
    Title of host publicationCAMSAP 2009 - 2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing
    Pages145-148
    Number of pages4
    DOIs
    StatePublished - Dec 1 2009
    Event2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2009 - Aruba, Netherlands
    Duration: Dec 13 2009Dec 16 2009

    Publication series

    NameCAMSAP 2009 - 2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing

    Other

    Other2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2009
    CountryNetherlands
    CityAruba
    Period12/13/0912/16/09

    Fingerprint

    Fusion reactions
    Systems analysis
    Sensor networks
    Signal to noise ratio

    All Science Journal Classification (ASJC) codes

    • Computational Theory and Mathematics
    • Computer Networks and Communications
    • Software

    Cite this

    Xiong, G., Kishore, S., & Yener, A. (2009). On low complexity cooperative spectrum sensing for cognitive networks. In CAMSAP 2009 - 2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (pp. 145-148). [5413316] (CAMSAP 2009 - 2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing). https://doi.org/10.1109/CAMSAP.2009.5413316
    Xiong, Gang ; Kishore, Shalinee ; Yener, Aylin. / On low complexity cooperative spectrum sensing for cognitive networks. CAMSAP 2009 - 2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing. 2009. pp. 145-148 (CAMSAP 2009 - 2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing).
    @inproceedings{9aaf3ca773764782a02f3a115b6be219,
    title = "On low complexity cooperative spectrum sensing for cognitive networks",
    abstract = "This paper presents a practical system design approach for cooperative spectrum sensing in cognitive sensor networks. An optimization problem is formulated, where the objective is to choose appropriate number of samples used in local energy calculation and linear combination weights for a global fusion center that together maximize global spectrum detection probability. Depending on the local information available to the fusion center and secondary users, practical system design is proposed in high fusion signal to noise ratio (SNR) regime, which has minimal implementation complexity and negligible performance loss, thus provides an efficient system design alternative in practice. Simulation results are presented to verify the analytical results.",
    author = "Gang Xiong and Shalinee Kishore and Aylin Yener",
    year = "2009",
    month = "12",
    day = "1",
    doi = "10.1109/CAMSAP.2009.5413316",
    language = "English (US)",
    isbn = "9781424451807",
    series = "CAMSAP 2009 - 2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing",
    pages = "145--148",
    booktitle = "CAMSAP 2009 - 2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing",

    }

    Xiong, G, Kishore, S & Yener, A 2009, On low complexity cooperative spectrum sensing for cognitive networks. in CAMSAP 2009 - 2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing., 5413316, CAMSAP 2009 - 2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, pp. 145-148, 2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2009, Aruba, Netherlands, 12/13/09. https://doi.org/10.1109/CAMSAP.2009.5413316

    On low complexity cooperative spectrum sensing for cognitive networks. / Xiong, Gang; Kishore, Shalinee; Yener, Aylin.

    CAMSAP 2009 - 2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing. 2009. p. 145-148 5413316 (CAMSAP 2009 - 2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing).

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

    TY - GEN

    T1 - On low complexity cooperative spectrum sensing for cognitive networks

    AU - Xiong, Gang

    AU - Kishore, Shalinee

    AU - Yener, Aylin

    PY - 2009/12/1

    Y1 - 2009/12/1

    N2 - This paper presents a practical system design approach for cooperative spectrum sensing in cognitive sensor networks. An optimization problem is formulated, where the objective is to choose appropriate number of samples used in local energy calculation and linear combination weights for a global fusion center that together maximize global spectrum detection probability. Depending on the local information available to the fusion center and secondary users, practical system design is proposed in high fusion signal to noise ratio (SNR) regime, which has minimal implementation complexity and negligible performance loss, thus provides an efficient system design alternative in practice. Simulation results are presented to verify the analytical results.

    AB - This paper presents a practical system design approach for cooperative spectrum sensing in cognitive sensor networks. An optimization problem is formulated, where the objective is to choose appropriate number of samples used in local energy calculation and linear combination weights for a global fusion center that together maximize global spectrum detection probability. Depending on the local information available to the fusion center and secondary users, practical system design is proposed in high fusion signal to noise ratio (SNR) regime, which has minimal implementation complexity and negligible performance loss, thus provides an efficient system design alternative in practice. Simulation results are presented to verify the analytical results.

    UR - http://www.scopus.com/inward/record.url?scp=77951104687&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=77951104687&partnerID=8YFLogxK

    U2 - 10.1109/CAMSAP.2009.5413316

    DO - 10.1109/CAMSAP.2009.5413316

    M3 - Conference contribution

    SN - 9781424451807

    T3 - CAMSAP 2009 - 2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing

    SP - 145

    EP - 148

    BT - CAMSAP 2009 - 2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing

    ER -

    Xiong G, Kishore S, Yener A. On low complexity cooperative spectrum sensing for cognitive networks. In CAMSAP 2009 - 2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing. 2009. p. 145-148. 5413316. (CAMSAP 2009 - 2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing). https://doi.org/10.1109/CAMSAP.2009.5413316