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
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 , and , 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.
|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:||17 Sep 2016 08:27|