DocumentCode
687967
Title
A new precoder design for precoding-based Blind channel estimation for MIMO-OFDM systems
Author
Song Noh ; Zoltowski, M.D.
Author_Institution
Sch. of Electr. & Comput. Eng., Purdue Univ., West Lafayette, IN, USA
fYear
2013
fDate
9-13 Dec. 2013
Firstpage
3306
Lastpage
3311
Abstract
Semi-Blind/Blind channel estimation for multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems has received a lot of attention in recent years. A new linear precoder for blind channel estimation is proposed in which only a small number of subcarriers carry symbols that are linearly precoded to effect the inter-symbol correlation needed for the blind channel estimation scheme to function properly. The proposed precoding scheme leaves most of the subcarriers intact, thereby minimizing the number of symbols that have to be jointly estimated via either Maximum Likelihood (ML) or MMSE. An optimal precoder under the sparse structure is developed, which insures that the precoder matrix is well-conditioned to minimize any noise enhancement that may occur in the process of MMSE based joint symbol estimation.
Keywords
MIMO communication; OFDM modulation; channel estimation; correlation methods; interference suppression; least mean squares methods; maximum likelihood estimation; precoding; sparse matrices; MIMO-OFDM system; MMSE process; intersymbol correlation; joint symbol estimation; maximum likelihood estimation; multiple-input multiple-output system; noise enhancement minimization; optimal linear precoder subcarrier; orthogonal frequency-division multiplexing system; precoder matrix; precoding-based blind channel estimation; semiblind channel estimation scheme; sparse structure; Blind equalizers; Channel estimation; Eigenvalues and eigenfunctions; Estimation; MIMO; Noise; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Global Communications Conference (GLOBECOM), 2013 IEEE
Conference_Location
Atlanta, GA
Type
conf
DOI
10.1109/GLOCOM.2013.6831582
Filename
6831582
Link To Document