Enhanced Two-Dimensional Data-aided Channel Estimation for TDS-OFDM

Ming Liu (1) , Matthieu Crussière (1) , Jean-François Hélard (2)

1 IETR - Institut d'Electronique et de Télécommunications de Rennes
2 IETR - Institut d'Électronique et des Technologies du numéRique

In time domain synchronous (TDS)-OFDM, the channel estimation is conventionally carried out based on the pseudo noise (PN) sequence. The PN sequence based channel estimation however suffers interference from adjacent OFDM data symbols. This paper proposes a new low-complexity dataaided channel estimation method with two-dimensional (2-D) estimate refinement and interpolation. Data-aided channel estimation is carried out using the rebuilt OFDM data symbols as virtual training symbols. In contrast to the classical turbo channel estimation, interleaving and decoding functions are not used when rebuilding OFDM data symbols thereby reducing the complexity. 2-D estimate refinement and interpolation are proposed to improve the data-aided channel estimation. Simulation results show that the performance of TDS-OFDM based DTMB system using the proposed method is very close to that with perfect channel estimation in terms of bit error rate (BER).

Mots clés: data-aided channel estimation; two-dimensional Wiener Filtering; TDS-OFDM; DTMB

Domaines: Réseaux et télécommunications [cs.NI]

Ming Liu, Matthieu Crussière, Jean-François Hélard. Enhanced Two-Dimensional Data-aided Channel Estimation for TDS-OFDM. The 4th International Conference on Signal Processing and Communication Systems (ICSPCS'2010), Dec 2010, Gold Coast, Australia. pp.1-6. ⟨hal-00541189⟩