DocumentCode
3330295
Title
Improved channel estimation using superimposed training
Author
Ghogho, Mounir ; Swami, Ananthram
Author_Institution
Sch. of Electr. & Electron. Eng., Leeds Univ., UK
fYear
2004
fDate
11-14 July 2004
Firstpage
110
Lastpage
114
Abstract
We establish identifiability conditions on the periodic training signals used in a superimposed scheme. Next, we consider optimal weighted channel estimators. We study the class of training signals that minimize the channel-averaged MSE; we then seek sequences in this class that minimize the peak-to-average power ratio.
Keywords
channel estimation; intersymbol interference; mean square error methods; minimisation; multipath channels; sequences; channel-averaged MSE; identifiability condition; optimal weighted channel estimator; peak-to-average power ratio; periodic training signal; superimposed training; Additive noise; Artificial intelligence; Channel estimation; Impedance; Interference; Multipath channels; Peak to average power ratio; Signal processing; Statistics; Wireless communication;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing Advances in Wireless Communications, 2004 IEEE 5th Workshop on
Print_ISBN
0-7803-8337-0
Type
conf
DOI
10.1109/SPAWC.2004.1439214
Filename
1439214
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