Collaborative Spectrum Sensing for Cognitive Radio: Diversity Combining Approach

DOI: 10.4236/wsn.2011.31004   PDF   HTML     5,389 Downloads   10,612 Views   Citations


In this paper it is shown that cyclostationary spectrum sensing for Cognitive Radio networks, applying multiple cyclic frequencies for single user detection can be interpreted (with some assumptions) in terms of optimal incoherent diversity addition for “virtual diversity branches” or SIMO radar. This approach allows proposing, by analogy to diversity combining, suboptimal algorithms which can provide near optimal characteristics for the Neyman-Pearson Test (NPT) for single user detection. The analysis is based on the Generalized Gaussian (Klovsky-Middleton) Channel Model, which allows obtaining the NPT noise immunity characteristics: probability of misdetection error (PM) and probability of false alarm (Pfa) or Receiver Operational Characteristics (ROC) in the most general way. Some quasi-optimum algorithms such as energetic receiver and selection addition algorithm are analyzed and their comparison with the noise immunity properties (ROC) of the optimum approach is provided as well. Finally, the diversity combining approach is applied for the collaborative spectrum sensing and censoring. It is shown how the diversity addition principles are applied for distributed detection algorithms, called hereafter as SIMO radar or distributed SIMO radar, implementing Majority Addition (MA) approach and Weighted Majority Addition (WMA) principle.

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O. Filio-Rodriguez, V. Kontorovich, S. Primak and F. Ramos-Alarcon, "Collaborative Spectrum Sensing for Cognitive Radio: Diversity Combining Approach," Wireless Sensor Network, Vol. 3 No. 1, 2011, pp. 24-37. doi: 10.4236/wsn.2011.31004.

Conflicts of Interest

The authors declare no conflicts of interest.


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