Application of Compressive Sensing for Estimating Sparse Multipaths Channel of MIMO Systems

Author

Jin, Ming ; Li, Youming

Author_Institution

Coll. of Inf. Sci. & Eng., Ningbo Univ., Ningbo, China

fYear

2011

fDate

16-18 Aug. 2011

Firstpage

1

Lastpage

4

Abstract

The compressive sensing (CS) theory can be applied for estimating the nonselective sparse multipath channel of multiple-input multiple-output (MIMO) systems. In this paper, a progressive refinement approach is given for alleviating the high computational load from high dimensions of basis matrix. Comparing with the least square (LS) estimating method, the presented algorithm is shown to be achieving a better performance. Finally, numerical simulations verify the proposed method.

Keywords

MIMO communication; channel estimation; least squares approximations; matrix algebra; multipath channels; numerical analysis; signal reconstruction; CS theory; LS estimation method; MIMO system; compressive sensing theory; least square estimation method; multiple-input multiple-output system; nonselective sparse multipath channel estimation; numerical simulation; progressive refinement approach; Channel estimation; Compressed sensing; Information science; MIMO; MIMO radar; Multipath channels; Signal processing;

fLanguage

English

Publisher

ieee

Conference_Titel

Internet Technology and Applications (iTAP), 2011 International Conference on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-7253-6

Type

conf

DOI

10.1109/ITAP.2011.6006114

Filename

6006114