Blind multiband spectrum signals reconstruction algorithms comparison

Author

Hao Shen ; Arildsen, Thomas ; Tandur, Deepaknath ; Larsen, Torben

Author_Institution

Dept. of Electron. Syst., Aalborg Univ., Aalborg, Denmark

fYear

2011

fDate

Aug. 29 2011-Sept. 2 2011

Firstpage

353

Lastpage

357

Abstract

This paper investigates sparse sampling techniques applied to downsampling and interference detection for multiband radio frequency (RF) signals. To reconstruct a signal from sparse samples is a compressive sensing problem. This paper compares three different reconstruction algorithms: 1) ℓ₁ minimization; 2) greedy pursuit; and 3) MUltiple SIgnal Classification (MUSIC). We compare the performance of these algorithms and investigate the robustness to noise effects. Characteristics and limitations of each algorithm are discussed.

Keywords

compressed sensing; interference (signal); minimisation; signal classification; signal reconstruction; spectral analysis; MUSIC; RF signal; blind multiband spectrum signal reconstruction algorithm; compressive sensing; greedy pursuit; interference detection; minimization algorithm; multiband radiofrequency signal; multiple signal classification; noise effect; sparse sampling technique; Algorithm design and analysis; Eigenvalues and eigenfunctions; Matching pursuit algorithms; Multiple signal classification; Signal to noise ratio; Vectors;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing Conference, 2011 19th European

Conference_Location

Barcelona

ISSN

2076-1465

Type

conf

Filename

7074103