Correlation-Statistics-Based Spectrum Sensing Exploiting Energy and Polarization for Dual-Polarized Cognitive Radios

PROJECT TITLE :

Correlation-Statistics-Based Spectrum Sensing Exploiting Energy and Polarization for Dual-Polarized Cognitive Radios

ABSTRACT:

In this paper, we consider the matter of spectrum sensing in cognitive radios by exploiting Stokes subvector, which can fully describe energy and polarization info of the received vector signal captured by twin-polarized antennas. We tend to 1st notice that each component correlation between Stokes variables (i.e., the weather of Stokes subvector) and vector correlation between Stokes subvectors containing signal and noise are different from that of noise solely with high chance. Therefore, 2 new blind detectors, specifically, component-correlation-based mostly energy-polarization detection (CCB-EPD) and vector-correlation-based energy-polarization detection (VCB-EPD), are proposed, respectively. The analysis results reveal that CCB-EPD and VCB-EPD are all constant false alarm rate detectors, and the VCB-EPD technique achieves better performance than CCB-EPD when channel is low depolarized and vice versa. Simulations show that the proposed two ways exhibit higher performances than other multiantenna-based mostly detectors whether or not priori polarization information of primary user is thought or not. We conjointly show that the 2 proposed ways have performance improvement with respect to existing polarization-primarily based detectors due to the exploitation of both energy and polarization information and also the unaffectedness by noise uncertainty. The experimental results verify that the proposed 2 ways will satisfy the performance demand specified by the IEEE 802.22 normal.

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