Title :
Iterative Synchronisation and DC-Offset Estimation using Superimposed Training
Author :
Moosvi, S.M.A. ; McLernon, Des C. ; Alameda-Hernandez, E.
Author_Institution :
Sch. of Electron. & Electr. Eng., Leeds Univ., UK
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 A.G. Orozco-Lugo et al. (2004), J.K. Tugnait and W. Luo (2004) and E. Alameda-Hernandez et al., 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 :
channel estimation; equalisers; error statistics; iterative methods; synchronisation; BER; DC-offset estimation; channel estimation; data noise; delay ambiguity; equaliser; iterative synchronisation; superimposed training; Bit error rate; Channel estimation; Delay effects; Delay estimation; Fading; Interference; Iterative algorithms; Iterative methods; Noise reduction; Polynomials; Estimation; Fading channels; Iterative methods; Synchronisation;
Conference_Titel :
Acoustics, Speech and Signal Processing, 2007. ICASSP 2007. IEEE International Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
1-4244-0727-3
DOI :
10.1109/ICASSP.2007.366517