An improved reconstruction technique for wavelet-based compressive spectrum sensing using genetic algorithm

Author

El-Khamy, Said E. ; Abdel-Malek, Mina B. ; Kamel, Sara H.

Author_Institution

Fac. of Eng., Alexandria Univ., Alexandria, Egypt

fYear

2014

fDate

28-30 April 2014

Firstpage

99

Lastpage

106

Abstract

In this paper we introduce the genetic algorithm as an improved method of signal reconstruction in wavelet-based compressive sensing. Instead of using basis pursuit for reconstruction, a population of initial guesses is created and a genetic algorithm is applied to find the sparsest solution. The paper investigates the different possible objective functions and constraints to give the best performance in a Cognitive Radio spectrum sensing framework.

Keywords

cognitive radio; compressed sensing; genetic algorithms; radio spectrum management; signal reconstruction; signal sampling; wavelet transforms; cognitive radio spectrum sensing; genetic algorithm; improved signal reconstruction method; subNyquist sampling; wavelet transform; wavelet-based compressive spectrum sensing; Compressed sensing; Genetic algorithms; Linear programming; Sensors; Vectors; Wavelet transforms; Wideband; Cognitive Radio; Compressive Sensing; Genetic Algorithm; Reconstruction; Spectrum Sensing; Sub-Nyquist Sampling; Wavelet Transform;

fLanguage

English

Publisher

ieee

Conference_Titel

Radio Science Conference (NRSC), 2014 31st National

Conference_Location

Cairo

Print_ISBN

978-1-4799-3820-9

Type

conf

DOI

10.1109/NRSC.2014.6835066

Filename

6835066