Permuted&Filtered Spectrum Compressive Sensing

Author

Biao Sun ; Qian Chen ; Xinxin Xu ; Yun He ; Jianjun Jiang

Author_Institution

Sch. of Opt. & Electron. Inf., Huazhong Univ. of Sci. & Technol., Wuhan, China

Volume

20

Issue

7

fYear

2013

fDate

Jul-13

Firstpage

685

Lastpage

688

Abstract

A permuted&filtered spectrum compressive sensing (PFSCS) method is developed for spectrum sparse signals. Using the permutation function and the flat window function, PFSCS first constructs the permuted&filtered measurement matrix and acquires the measurements vector. Then PFSCS locates and estimates fourier coefficients using the two samples method which has been used in orthogonal frequency division multiplexing (OFDM). Experimental results show that PFSCS runs much faster and performs better than standard compressive sensing methods, especially when the sparsity K is high.

Keywords

OFDM modulation; compressed sensing; filtering theory; signal detection; Fourier coefficient; OFDM; filtered spectrum compressive sensing; flat window function; measurement matrix; measurements vector; orthogonal frequency division multiplexing; permutation function; permuted spectrum compressive sensing; spectrum sparse signal; Compressed sensing; Computational complexity; Matching pursuit algorithms; Signal processing algorithms; Signal to noise ratio; Sparse matrices; Standards; Compressive sensing; PFSCS; permuted&filtered matrix; spectrum compressive sensing;

fLanguage

English

Journal_Title

Signal Processing Letters, IEEE

Publisher

ieee

ISSN

1070-9908

Type

jour

DOI

10.1109/LSP.2013.2258464

Filename

6502765