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

Research Article

A Discrete-Time Multi-server Model for Opportunistic Spectrum Access Systems

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  • @INPROCEEDINGS{10.1007/978-3-319-24540-9_31,
        author={Islam Maksoud and Sherif Rabia},
        title={A Discrete-Time Multi-server Model for Opportunistic Spectrum Access Systems},
        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={Discrete-time queueing Multi-server Cognitive radio Opportunistic spectrum access},
        doi={10.1007/978-3-319-24540-9_31}
    }
    
  • Islam Maksoud
    Sherif Rabia
    Year: 2015
    A Discrete-Time Multi-server Model for Opportunistic Spectrum Access Systems
    CROWNCOM
    Springer
    DOI: 10.1007/978-3-319-24540-9_31
Islam Maksoud1,*, Sherif Rabia1,*
  • 1: Alexandria University
*Contact email: islammax@alexu.edu.eg, sherif.rabia@alexu.edu.eg

Abstract

In opportunistic spectrum access communication systems, secondary users (SUs) exploit the spectrum holes not used by the primary users (PUs) and cease their transmissions whenever primary users reuse their spectrum bands. To study the mean time an SU spends in the system we propose a discrete-time multi-server access model. Since periodic sensing is commonly used to protect the PU, discrete-time models are more convenient to analyze the performance of the SU system. Additionally, a multi-server access model is assumed in order to give the SU the capability to access a channel that is not occupied by a PU or any other SUs. We derive the probability generating function of the number of connections in the system. Then we derive a formula for the mean response time of an SU. In the numerical results we show the relationship between the mean response time and the SU traffic intensity. In addition we show the effect of changing the number of channels in the system and the PU traffic intensity on the mean response time of an SU.