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Sensors 2017, 17(5), 1052; doi:10.3390/s17051052

Spectrum Sensing Using Co-Prime Array Based Modulated Wideband Converter

1
School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China
2
College of Communications Engineering, PLA University of Science and Technology, Nanjing 210007,China
*
Author to whom correspondence should be addressed.
Academic Editors: Francisco Javier Falcone Lanas, Ana Alejos and Leyre Azpilicueta
Received: 6 March 2017 / Revised: 29 April 2017 / Accepted: 2 May 2017 / Published: 6 May 2017
(This article belongs to the Special Issue Cognitive Radio Sensing and Sensor Networks)
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Abstract

As known to us all, it is challenging to monitor wideband signals in frequency domain due to the restriction of hardware. Several practical sampling schemes, such as multicoset sampling and the modulated wideband converter (MWC), have been proposed. In this work, a co-prime array (CA) based modulated wideband converter (MWC) spectrum sensing method is suggested. Our proposed method has the same sampling principle as the MWC but has some advantages compared to MWC. Firstly, CA-based MWC is an array-based MWC system. Each sensor is usually corrupted by independent noise for an array system which can be used for noise averaging, while all channels in conventional MWC have the same receiving noise. Secondly, by incorporating the co-prime array, we can estimate the power spectrum of signal directly employing its second-order statistical properties. Moreover, the system minimal sampling rate can be reduced further because of the reduction of sampling channels. Simulation results show that our method has better performance than traditional methods. View Full-Text
Keywords: co-prime array; modulated wideband converter; spectrum sensing; minimal sampling rate co-prime array; modulated wideband converter; spectrum sensing; minimal sampling rate
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Lv, W.; Wang, H.; Mu, S. Spectrum Sensing Using Co-Prime Array Based Modulated Wideband Converter. Sensors 2017, 17, 1052.

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