Blind identification of sparse SIMO channels using maximum a posteriori approach

Abdeldjalil Aissa El Bey (1, 2) , Karim Abed-Meraim (3)

1 Lab-STICC_TB_CACS_COM
2 SC - Département Signal et Communications
3 ENST - Ecole Nationale Supérieure des Télécommunications

In this paper, we are interested in blind identification of sparse single-input multiple-output (SIMO) systems. A maximum a posteriori approach is considered using generalized Laplacian distribution for the channel coefficients. This leads to a cost function given by the deterministic maximum likelihood (ML) criterion penalized by 'a sparsity measure' term expressed by the Lp norm of the channel coefficient vector. A simple but efficient optimization algorithm using gradient technique with optimal step-size is proposed. The simulations show that the proposed method outperforms the ML technique in terms of estimation error and is robust against channel order overestimation errors.

Mots clés: Blind identification; Sparse channel

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

Abdeldjalil Aissa El Bey, Karim Abed-Meraim. Blind identification of sparse SIMO channels using maximum a posteriori approach. EUSIPCO 2008 : 16th European Signal Processing Conference, Aug 2009, Lausanne, Switzerland. ⟨hal-01770993⟩