Channel Estimation for MIMO-OFDM Systems in Fast Time-Varying Environments

Hussein Hijazi (1, 2) , Eric Pierre Simon (1) , M. Lienard (1) , Laurent Ros (3)

1 IEMN - Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520
2 GIPSA-lab - Grenoble Images Parole Signal Automatique
3 GIPSA-CICS - GIPSA - Communication Information and Complex Systems

A channel estimation algorithm for MIMO-OFDM systems in Fast Time-Varying Environments is proposed. The channel estimation function is based on the equivalent discrete-time channel taps or on the physical propagation channel parameters. To handle rapid variations of channels within a transmission block, we approximate the channel by a basis expansion model (BEM). Based on the Jakes process, an auto-regressive (AR) model of the BEM coefficients dynamics is built, making it possible to estimate and track the BEM coefficients using Kalman filter. Hence, the channel matrix is easily computed, and the data symbol is detected with free ICI . Our claims are supported by theoretical analysis and simulation results, which are obtained considering Jakes' channels with high Doppler spreads.

Mots clés: Basis Expansion Model (BEM); MIMO systems; OFDM; time-varying Rayleigh channels; channel estimation; Kalman filter; Basis Expansion Model (BEM).

Domaines: Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Hussein Hijazi, Eric Pierre Simon, M. Lienard, Laurent Ros. Channel Estimation for MIMO-OFDM Systems in Fast Time-Varying Environments. ISCCSP 2008 - 4th International Symposium on Communications, Control and Signal Processing, Mar 2010, Limassol, Cyprus. 5 p., ⟨10.1109/ISCCSP.2010.5463392⟩. ⟨hal-00539137⟩