An effective wideband spectrum sensing method based on L1-SVD algorithm

Author

Fulai Liu ; Ruiyan Du

Author_Institution

Northeastern Univ., Shenyang, China

fYear

2014

fDate

19-23 Oct. 2014

Firstpage

83

Lastpage

87

Abstract

This paper presents an effective wideband spectrum sensing method based on compressed sensing theory. By making use of temporal smoothing technique, the proposed approach gives an effective sparse signal representation method for wideband spectrum sensing problem. After that, the proposed method can effectively obtain the sparse coefficients by L1-SVD algorithm so that all spectral holes can be detected. Finally, several simulation results are presented to testify the effectiveness of the proposed approach.

Keywords

cognitive radio; compressed sensing; radio spectrum management; signal representation; singular value decomposition; L1-SVD algorithm; cognitive radio networks; compressed sensing theory; sparse coefficients; sparse signal representation method; spectral hole detection; temporal smoothing technique; wideband spectrum sensing method; Abstracts; Algorithm design and analysis; Indexes; Sensors; Smoothing methods; Cognitive radio; Compressed sensing; L1-SVD; Temporal smoothing; Wideband spectrum sensing;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing (ICSP), 2014 12th International Conference on

Conference_Location

Hangzhou

ISSN

2164-5221

Print_ISBN

978-1-4799-2188-1

Type

conf

DOI

10.1109/ICOSP.2014.7014974

Filename

7014974