Research Article
Support Recovery for Multiband Spectrum Sensing Based on Modulated Wideband Converter with SwSOMP Algorithm
@INPROCEEDINGS{10.1007/978-3-319-72823-0_15, author={Zhuhua Hu and Yong Bai and Yaochi Zhao and Yiran Zhang}, title={Support Recovery for Multiband Spectrum Sensing Based on Modulated Wideband Converter with SwSOMP Algorithm}, proceedings={5G for Future Wireless Networks. First International Conference, 5GWN 2017, Beijing, China, April 21-23, 2017, Proceedings}, proceedings_a={5GWN}, year={2018}, month={1}, keywords={Spectrum sensing MWC sub-Nyquist sampling Compressed sensing Stage-wise weak Simultaneous OMP(SwSOMP)}, doi={10.1007/978-3-319-72823-0_15} }- Zhuhua Hu
Yong Bai
Yaochi Zhao
Yiran Zhang
Year: 2018
Support Recovery for Multiband Spectrum Sensing Based on Modulated Wideband Converter with SwSOMP Algorithm
5GWN
Springer
DOI: 10.1007/978-3-319-72823-0_15
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.