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IEEE Transactions on Broadcasting 58, 2 (2012) 247-260
A Novel Data-Aided Channel Estimation with Reduced Complexity for TDS-OFDM Systems
Ming Liu 1, Matthieu Crussière 1, Jean-François Hélard 1
(01/03/2012)

In contrast to the classical cyclic prefix (CP)-OFDM, the time domain synchronous (TDS)-OFDM employs a known pseudo noise (PN) sequence as guard interval (GI). Conventional channel estimation methods for TDS-OFDM are based on the exploitation of the PN sequence and consequently suffer from intersymbol interference (ISI). This paper proposes a novel dataaided channel estimation method which combines the channel estimates obtained from the PN sequence and, most importantly, additional channel estimates extracted from OFDM data symbols. Data-aided channel estimation is carried out using the rebuilt OFDM data symbols as virtual training sequences. In contrast to the classical turbo channel estimation, interleaving and decoding functions are not included in the feedback loop when rebuilding OFDM data symbols thereby reducing the complexity. Several improved techniques are proposed to refine the data-aided channel estimates, namely one-dimensional (1-D)/two-dimensional (2-D) moving average and Wiener filtering. Finally, the MMSE criteria is used to obtain the best combination results and an iterative process is proposed to progressively refine the estimation. Both MSE and BER simulations using specifications of the DTMB system are carried out to prove the effectiveness of the proposed algorithm even in very harsh channel conditions such as in the single frequency network (SFN) case.
1 :  Institut d'Electronique et de Télécommunications de Rennes (IETR)
CNRS : UMR6164 – Université de Rennes 1 – Institut National des Sciences Appliquées (INSA) - Rennes – SUPELEC – Université de Nantes
Systèmes de communications numériques (SCN)
Informatique/Réseaux et télécommunications
TV broadcasting – channel estimation – OFDM – iterative method
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