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Iterative synchronisation and DC-offset estimation using superimposed training

Moosvi, S.M.A., McLernon, D.C. and Alameda-Hernandez, E. (2007) Iterative synchronisation and DC-offset estimation using superimposed training. In: IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 15 - 20 April, 2007, Honolulu, Hawaii, USA. IEEE , pp. 241-244. ISBN 1-4244-0728-1

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Abstract

In this paper, we propose a new iterative approach for superimposed training (ST) that improves synchronisation, DC-offset estimation and channel estimation. While synchronisation algorithms for ST have previously been proposed in [2],[4] and [5], due to interference from the data they performed sub-optimally, resulting in channel estimates with unknown delays. These delay ambiguities (also present in the equaliser) were estimated in previous papers in a non-practical manner. In this paper we avoid the need for estimation of this delay ambiguity by iteratively removing the effect of the data “noise”. The result is a BER performance superior to all other ST algorithms that have not assumed a-priori synchronisation.

Item Type: Proceedings Paper
Keywords: Superimposed Training, channel estimation, synchronisation
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Institute of Integrated Information Systems (Leeds)
Depositing User: Syed M A Moosvi
Date Deposited: 18 May 2007
Last Modified: 21 Nov 2014 11:44
Published Version: http://dx.doi.org/10.1109/ICASSP.2007.366517
Status: Published
Publisher: IEEE
Refereed: No
Identification Number: doi: 10.1109/ICASSP.2007.366517
Related URLs:
URI: http://eprints.whiterose.ac.uk/id/eprint/2485

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