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Sensors 2018, 18(7), 2222; https://doi.org/10.3390/s18072222

Wideband Spectrum Sensing Based on Single-Channel Sub-Nyquist Sampling for Cognitive Radio

1
School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
2
National Key Laboratory of Science and Technology on Communications, University of Electronic Science and Technology of China, Chengdu 611731, China
*
Author to whom correspondence should be addressed.
Received: 24 April 2018 / Revised: 29 June 2018 / Accepted: 3 July 2018 / Published: 10 July 2018
(This article belongs to the Section Sensor Networks)
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Abstract

Spectrum sensing is an important task in cognitive radio. However, currently available Analog-to-Digital Converters (ADC) can hardly satisfy the sampling rate requirement for wideband signals. Even with such an ADC, the cost is extremely high in terms of price and power consumption. In this paper, we propose a spectrum-sensing method based on single-channel sub-Nyquist sampling. Firstly, a serial Multi-Coset Sampling (MCS) structure is designed to avoid mismatches among sub-ADCs in the traditional parallel MCS. Clocks of the sample/hold and ADC are provided by two non-uniform sampling clocks. The cooperation between these two non-uniform sampling clocks shifts the high sampling rate burden from the ADC to the sample/hold. Secondly, a power spectrum estimation method using sub-Nyquist samples is introduced, and an efficient spectrum-sensing algorithm is proposed. By exploiting the frequency-smoothing property, the proposed efficient spectrum-sensing algorithm only needs to estimate power spectrum at partial frequency bins to conduct spectrum sensing, which will save a large amount of computational cost. Finally, the sampling pattern design of the proposed serial MCS is given, and it is proved to be a minimal circular sparse ruler with an additional constraint. Simulations show that mismatches in traditional parallel MCS have a serious impact on spectrum-sensing performance, while the proposed serial MCS combined with the efficient spectrum-sensing algorithm exhibits outstanding spectrum-sensing performance at much lower computational cost. View Full-Text
Keywords: cognitive radio; spectrum sensing; single-channel sub-Nyquist sampling; multi-coset sampling; sampling pattern design; minimal circular sparse ruler cognitive radio; spectrum sensing; single-channel sub-Nyquist sampling; multi-coset sampling; sampling pattern design; minimal circular sparse ruler
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Liu, C.; Wang, H.; Zhang, J.; He, Z. Wideband Spectrum Sensing Based on Single-Channel Sub-Nyquist Sampling for Cognitive Radio. Sensors 2018, 18, 2222.

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