Cognitive Radio Oriented Wireless Networks. 10th International Conference, CROWNCOM 2015, Doha, Qatar, April 21–23, 2015, Revised Selected Papers

Research Article

Fractional Low Order Cyclostationary-Based Spectrum Sensing in Cognitive Radio Networks

Download
310 downloads
  • @INPROCEEDINGS{10.1007/978-3-319-24540-9_1,
        author={Hadi Hashemi and Sina Fard and Abbas Taherpour and Tamer Khattab},
        title={Fractional Low Order Cyclostationary-Based Spectrum Sensing in Cognitive Radio Networks},
        proceedings={Cognitive Radio Oriented Wireless Networks. 10th International Conference, CROWNCOM 2015, Doha, Qatar, April 21--23, 2015, Revised Selected Papers},
        proceedings_a={CROWNCOM},
        year={2015},
        month={10},
        keywords={Cognitive radio Spectrum sensing Cyclostationary signal Fractional low order},
        doi={10.1007/978-3-319-24540-9_1}
    }
    
  • Hadi Hashemi
    Sina Fard
    Abbas Taherpour
    Tamer Khattab
    Year: 2015
    Fractional Low Order Cyclostationary-Based Spectrum Sensing in Cognitive Radio Networks
    CROWNCOM
    Springer
    DOI: 10.1007/978-3-319-24540-9_1
Hadi Hashemi1,*, Sina Fard1, Abbas Taherpour1, Tamer Khattab2,*
  • 1: Imam Khomeini International University
  • 2: Qatar University
*Contact email: h.hashemi@edu.ikiu.ac.ir, tkhattab@ieee.org

Abstract

In this paper, we study the problem of cyclostationary spectrum sensing in cognitive radio networks based on cyclic properties of linear modulations. For this purpose, we use fractional order of observations in cyclic autocorrelation function (CAF).We derive the generalized likelihood ratio (GLR) for designing the detector. Therefore, the performance of this detector has been improved compared to previous detectors. We also find optimum value of the fractional order of observations in additive Gaussian noise. The exact performance of the GLR detector is derived analytically as well. The simulation results are presented to evaluate the performance of the proposed detector and compare its performance with their counterpart, so to illustrate the impact of the optimum value of fractional order over performance improvement of these detectors.