Abstract
The Modulated Wideband Converter (MWC) can provide a sub-Nyquist sampling approach to sense sparse multiband analog signals and reconstruct the frequency support set. However, the existing SOMP reconstruction algorithms need a priori information of signal sparsity. This paper applies the SwOMP algorithm to the CTF (Continuous-To-Finite) block of MWC. The SwSOMP algorithm uses stage-wise weak selection in SOMP, and it can reduce computational cost and solve large scale problems. It does not need prior information of signal sparsity, and the frequency support can be reconstructed blindly. The simulation results demonstrate that, MWC system with SwSOMP algorithm, compared with the SOMP algorithm, can use less number of channels, achieve higher percentage of correct support recovery blindly, and reduce the sampling rate of the system.
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Acknowledgments
This paper was supported by the National Natural Science Foundation of China (Grant No. 61561017), Open Sub-project of State Key Laboratory of Marine Resource Utilization in South China Sea (Grant No. 2016013B), Hainan Province Natural Science Foundation of China (Grant No. 617033), Doctoral Candidate Excellent Dissertation Cultivating Project of Hainan University, and Postgraduate Practice and Innovation Project of Hainan University. Oriented Project of State Key Laboratory of Marine Resource Utilization in South China Sea (Grant No. DX2017012).
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Hu, Z., Bai, Y., Zhao, Y., Zhang, Y. (2018). Support Recovery for Multiband Spectrum Sensing Based on Modulated Wideband Converter with SwSOMP Algorithm. In: Long, K., Leung, V., Zhang, H., Feng, Z., Li, Y., Zhang, Z. (eds) 5G for Future Wireless Networks. 5GWN 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 211. Springer, Cham. https://doi.org/10.1007/978-3-319-72823-0_15
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DOI: https://doi.org/10.1007/978-3-319-72823-0_15
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