In this paper, an adaptive multi-channel energy detector is presented for spectrum sensing applications. This method exploits the Empirical Mode Decomposition (EMD) and Cell-Averaging Constant False Alarm Rate (CA-CFAR) in an effort to maximize the probability of detection for a given probability of false alarm. First, the oversampled baseband signal is compared to its corresponding EMD noise-only model. If the band is occupied, then an EMD-CA technique is used to estimate the noise power for a given false alarm probability. Then, from the estimated noise power, double thresholds based on two given false alarm rates are calculated to detect and localize the occupied channels of band of interest. The proposed approach is able to work blindly and it is independent of the noise power. Simulations for different sampling and false alarm rates are used to validate the performance of the proposed detector. The results revealed the robustness of the proposed technique to the noise uncertainty and the capability to sense and localize multiple channels simultaneously.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    An EMD-Based Double Threshold Detector for Spectrum Sensing in Cognitive Radio Networks


    Contributors:


    Publication date :

    2015-09-01


    Size :

    132966 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




    On Reducing Multiband Spectrum Sensing Duration for Cognitive Radio Networks

    Soltani, Morteza / Baykas, Tuncer / Arslan, Huseyin | IEEE | 2016



    Multi-Band Cooperative Spectrum Sensing in RF Powered Cognitive Radio Networks

    Basharat, Mehak / Ejaz, Waleed / Raahemifar, Kaamran et al. | IEEE | 2016


    Cooperative Spectrum Sensing in Cognitive Radio Systems

    Zheng, Xueqiang / Cui, Li / Chen, Juan et al. | IEEE | 2008