Title
Channel estimation and symbol detection for block transmission using data-dependent superimposed training
Abstract
We address the problem of frequency-selective channel estimation and symbol detection using superimposed training. The superimposed training consists of the sum of a known sequence and a data-dependent sequence that is unknown to the receiver. The data-dependent sequence cancels the effects of the unknown data on channel estimation. The performance of the proposed approach is shown to significantly outperform existing methods based on superimposed training (ST).
Year
DOI
Venue
2005
10.1109/LSP.2004.842283
IEEE Signal Processing Letters
Keywords
Field
DocType
channel estimation,multipath channels,radio receivers,block transmission,data-dependent superimposed training,frequency-selective channel,symbol detection,estimation,superimposed training
Multipath channels,Transmission (mechanics),Symbol,Data dependent,Delay spread,Communication channel,Speech recognition,Radio receiver,Mathematics
Journal
Volume
Issue
ISSN
12
3
1070-9908
Citations 
PageRank 
References 
81
4.03
5
Authors
4
Name
Order
Citations
PageRank
Mounir Ghogho11072113.80
Desmond C. McLernon216115.18
Alameda-Hernandez, E.31057.30
Swami, A.45105566.62