DocumentCode
2088546
Title
Unified ML channel estimator for MIMO-OFDM systems with virtual carriers
Author
Zheng, Kang ; Tian, Feng ; Huang, Guowen ; Min Bei
fYear
2010
fDate
11-14 Nov. 2010
Firstpage
409
Lastpage
412
Abstract
In this paper, we study the Maximum Likelihood (ML) channel estimation for MIMO-OFDM systems with virtual carriers. A unified ML channel (UML) estimator is proposed to overcome performance loss caused by virtual carriers. The UML is a generalized algorithm applied to both pilot-aided and preamble based systems with arbitrarily placed virtual carriers. To reduce the complexity, Speeded and Compressed ML channel estimation (SCML) is proposed reduce both implementation storage and calculation complexity, to 26% of origin under 4G Gbits V-BLAST MIMO-OFDM system with good performance.
Keywords
MIMO communication; OFDM modulation; channel estimation; maximum likelihood estimation; MIMO-OFDM systems; V-BLAST; maximum likelihood channel estimator; pilot-aided based systems; preamble based systems; virtual carriers; Channel estimation; Radio access networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Communication Technology (ICCT), 2010 12th IEEE International Conference on
Conference_Location
Nanjing
Print_ISBN
978-1-4244-6868-3
Type
conf
DOI
10.1109/ICCT.2010.5688827
Filename
5688827
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