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 Apr 2007, Honolulu, Hawaii, USA. IEEE , pp. 241-244. ISBN 1-4244-0728-1
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.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Keywords: | Superimposed Training, channel estimation, synchronisation |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Institute of Communication & Power Networks (Leeds) |
Depositing User: | Syed M A Moosvi |
Date Deposited: | 18 May 2007 |
Last Modified: | 19 Dec 2022 13:19 |
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: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:2485 |