DocumentCode :
1094045
Title :
Joint ML time-frequency synchronisation and channel estimation algorithm for MIMO-OFDM systems
Author :
Saemi, A. ; Meghdadi, V. ; Cances, J.-P. ; Zahabi, M.R.
Author_Institution :
ENSIL, Limoges Univ., Limoges
Volume :
2
Issue :
1
fYear :
2008
fDate :
2/1/2008 12:00:00 AM
Firstpage :
103
Lastpage :
111
Abstract :
The maximum-likelihood (ML) time-frequency synchronisation algorithm combined with channel estimation for multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) systems in frequency selective fading channels is addressed. In the proposed algorithm, the authors use two steps to maximise an ML metric to obtain first the frequency offset and then timing. A fast Fourier transform algorithm is used to estimate the frequency offset. Using these two estimates, the channel is identified. A simple iterative algorithm is proposed to improve the frequency offset estimation. The performance of the proposed synchronisation approach, in terms of timing failure probability and mean square error of the estimated frequency offset and bit error rate, is compared with others in the literature. Comparison of simulation results with the Cramer-Rao lower bound clearly illustrates the accuracy of the proposed algorithm, which outperforms the state-of-the-art synchroniser devices in the open literature.
Keywords :
MIMO systems; OFDM modulation; channel estimation; fading channels; fast Fourier transforms; iterative methods; maximum likelihood estimation; mean square error methods; probability; synchronisation; time-frequency analysis; Cramer-Rao lower bound; MIMO-OFDM system; channel estimation algorithm; fast Fourier transform algorithm; frequency offset estimation; frequency selective fading channel; iterative algorithm; joint maximum likelihood time-frequency synchronisation; mean square error method; multiple input multiple output-orthogonal frequency division multiplexing; timing failure probability;
fLanguage :
English
Journal_Title :
Circuits, Devices & Systems, IET
Publisher :
iet
ISSN :
1751-858X
Type :
jour
DOI :
10.1049/iet-cds:20070024
Filename :
4464148
Link To Document :
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