Decoding Real-Field Codes by an Iterative Expectation-Maximization (EM) Algorithm

Hadi Zayyani (1) , Massoud Babaie-Zadeh (1) , Christian Jutten (2)

1 EE department of SUT [Tehran] - Department of Electrical Engineering [Tehran]
2 GIPSA-SIGMAPHY - GIPSA - Signal Images Physique

In this paper, a new approach for decoding real-field codes based on finding sparse solutions of underdetermined linear systems is proposed. This algorithm iteratively estimates the positions and the amplitudes of the sparse errors (or noise impulses using an Expectation-Maximization (EM) algorithm. Iterative estimation of amplitudes is done in the Expectation step (E-step), while iterative estimation of error positions is done in the Maximization step (M-step). Simulation results show 1-2 dB improvement over Linear Programming (LP) which has been previously used for error correction.

Mots clés: impulsive noise cancelation; sparse component analysis; Error correcting codes; sparse decomposition

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

Hadi Zayyani, Massoud Babaie-Zadeh, Christian Jutten. Decoding Real-Field Codes by an Iterative Expectation-Maximization (EM) Algorithm. ICASSP 2008 - IEEE International Conference on Acoustics, Speech and Signal Processing, Mar 2008, Las Vegas, United States. pp.3169-3172. ⟨hal-00271360⟩