Bayesian Compressive Spectrum Sensing Based on Dual Polarization Antenna

SU Kun; SUN Xuekang

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Bayesian Compressive Spectrum Sensing Based on Dual Polarization Antenna

SU Kun 1 #,SUN Xuekang 2 *

1.School of Network Education, Beijing University of Posts and Telecommunications

2.School of Network Education, Beijing University of Posts and Telecommunications

*Correspondence author

#Submitted by

Subject:

Funding: Chinese National Nature Science Foundation （No.No.61372116）

Opened online:23 September 2016

Accepted by: none

Citation: SU Kun,SUN Xuekang.Bayesian Compressive Spectrum Sensing Based on Dual Polarization Antenna[OL]. [23 September 2016] http://en.paper.edu.cn/en_releasepaper/content/4705119

The application of Bayesian Compressive Sensing framework to spectrum sensing has successfully attracted much attention, as it can sample sparse signals at sub-Nyquist rates in wideband cognitive radio network (CRN) to alleviate the bandwidth requirements on the hardware of most receivers. But it takes a long time to make signal parameter estimation recursively for the sparse signal recovery especially in the dual polarization antenna system. In this paper, Bayesian compressive spectrum sensing based on a dual polarization antenna receiving system is proposed to increase the accuracy and efficiency of the signal detection. In this scheme, we firstly make a combination of the two compressive signals received in both horizontal and vertical polarization directions by using the proposed angle weight combining (AWC) model, and then recover the combined signal. The approach is different from the traditional recovery operations which recover the received signals in both horizontal and vertical polarization directions respectively. Furthermore, the simulation results show that it has better performance and lower complexity compared with traditional methods.

Keywords:Bayesian compressed sensing; dual polarization antenna; spectrum sensing; polarization angle; complexity

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