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Synchronisation of the superimposed training method for channel estimation in the presence of DC-offset

By E. Alameda-Hernandez, D.C. McLernon, S.M.A Moosvi, M.M. Lara, A.G. Orozco-Lugo and M. Ghogho

Abstract

The superimposed training method estimates the channel\ud from the induced first-order cyclostationary statistics\ud exhibited by the received signal. In this paper,\ud using vector space decomposition, we show that the\ud information needed for training sequence synchronisation,\ud and for DC-offset estimation, can be extracted\ud from the first-order cyclostationary statistics as well.\ud Necessary and sufficient conditions for channel computation\ud and equalisation are derived, when training\ud sequence synchronisation and DC-offset removal are\ud required. The computational burden of the practical\ud implementation of the method presented here is much\ud lighter than for existing algorithms. At the same time,\ud simulation results show that the performance, in terms\ud of the MSE of the channel estimates and BER, is not\ud diminishedwhen compared to these existing algorithms

Year: 2005
OAI identifier: oai:eprints.whiterose.ac.uk:2482

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