Traffic Analysis of a Cognitive Radio Network Based on the Concept of Medium Access Probability
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The performance of a cognitive radio network (CRN) solely depends on howprecisely the secondary users can sense the presence or absence of primary users. Theincorporation of a spatial false alarm makes deriving the probability of a correctdecision a cumbersome task. Previous literature performed this task for the case of areceived signal under a Normal probability density function case. In this paper weenhance the previous work, including the impact of carrier frequency, the gain ofantennas on both sides, and antenna heights so as to observe the robustness againstnoise and interference and to make the correct decision of detection. Three small scalefading channels: Rayleigh, Normal, and Weibull were considered to get the real scenarioof a CRN in an urban area. The incorporation of a maximal-ratio combining and selectioncombing with a variation of the number of received antennas have also been studied inorder to achieve the correct decision of spectral sensing, so as to serve the cognitiveusers. Finally, we applied the above concept to a traffic model of the CRN, which webased on a two-dimensional state transition chain.
Abstract
The performance of a cognitive radio network (CRN) solely depends on howprecisely the secondary users can sense the presence or absence of primary users. Theincorporation of a spatial false alarm makes deriving the probability of a correctdecision a cumbersome task. Previous literature performed this task for the case of areceived signal under a Normal probability density function case. In this paper weenhance the previous work, including the impact of carrier frequency, the gain ofantennas on both sides, and antenna heights so as to observe the robustness againstnoise and interference and to make the correct decision of detection. Three small scalefading channels: Rayleigh, Normal, and Weibull were considered to get the real scenarioof a CRN in an urban area. The incorporation of a maximal-ratio combining and selectioncombing with a variation of the number of received antennas have also been studied inorder to achieve the correct decision of spectral sensing, so as to serve the cognitiveusers. Finally, we applied the above concept to a traffic model of the CRN, which webased on a two-dimensional state transition chain.
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