Exploring the Application of Random Sampling in Spectrum Sensing

  • Hayat Semlali
  • Najib Boumaaz
  • Asmaa Maali
  • Abdallah Soulmani
  • Abdelilah Ghammaz
  • Jean-François Diouris
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 27)


In cognitive radio (CR), a transmitter/receiver can detect intelligently the communication channels that are in use and those that are not, and can move in the unused channels. This can be achieved by the means of spectrum sensing (SS) operation. The concept in spectrum sensing aims to maximize the use of available radio frequencies of the spectrum while minimizing interference with other users. Different techniques are presented in the literature. In this paper, we proposed a spectrum sensing approach based on the energy detector (ED) method combined with random sampling. This approach is performed in cognitive radio systems to analyze the occupancy of radio frequency spectrum. The performance of the proposed approach is evaluated in terms of the false alarm probability and compared to the uniform sampling case in order to show the utility of the use of random sampling. To complete our theoretical and simulation study, we are interested in the implementation of our solution using a real FM radio signal. The analyzed signal is an FM radio signal captured under GNU-radio environment. The performance of this application is evaluated in terms of the receiver operating characteristic curves (ROC curves) and in terms of the false alarm probability for different values of signal to noise ratio (SNR) in order to demonstrate the feasibility of spectrum sensing operation with a random sampling mode. The obtained results show that random sampling makes it possible to overcome forbidden band restriction encountered with uniform sampling mode.


Cognitive radio Energy detector Implementation Random sampling Spectrum sensing 


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Hayat Semlali
    • 1
  • Najib Boumaaz
    • 1
  • Asmaa Maali
    • 1
  • Abdallah Soulmani
    • 1
  • Abdelilah Ghammaz
    • 1
  • Jean-François Diouris
    • 2
  1. 1.Laboratory of Electrical Systems and Telecommunications, Faculty of Sciences and TechnologyCadi Ayyad UniversityMarrakechMorocco
  2. 2.Department Electronic and Telecommunications Institute of Rennes (IETR – UMR 6164)Polytechnic School of the University of NantesNantesFrance

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