Preface The Noisy Channel Coding Theorem discovered by C. E. Shannon in 1948 offered communication engineers the possibility of reducing error rates on noisy channels to negligible levels without sacrificing data rates. The primary obstacle to the practical use of this theorem has been the equipment complexity and the computation time required to decode the noisy received data.

For high density magnetic recording channels and memory systems, low-density parity-check (LDPC) codes with probabilistic decoding are replacing Reed-Solomon (RS) codes or Bose-Chaudhuri-Hocquenghem (BCH) codes with conventional algebraic decoding. The main benefit of LDPC codes over the RS and BCH

Low-density parity-check codes are studied over Markov channels with time-varying gaussian or bit-flipping noise. The belief propagation decoding algorithm is extended to include channel estimation and the gains this extension produce are experimentally determined.

This paper looks at replacing the R-S code component of the SCRSCC with a low-density parity-check (LDPC) code [8]. A LDPC code used alone is a good code

In this paper a formal theory, construction methods, and a random ensemble approach for low-density parity-check convolutional codes (including turbo-codes) are presented. The principles of iterative decoding of low-density parity-check (LDPC) convolutional codes are given, and an iterative

This article summarizes a comparison of numerous low-density parity-check

Efficient low-density parity-check codes for cooperative communication

Low-density parity-check (LDPC) codes are forward error-correction codes, first proposed in the 1962 PhD thesis of Gallager at MIT. At the time, their incredible potential remained undiscovered due to the computational demands of simulation in an era when vacumm tubes were only just being replaced by

This survey guides the reader through the extensive open literature that is covering the family of low-density parity-check (LDPC) codes and their rateless relatives. In doing so, we will identify the most important milestones that have occurred since their conception until the current era

Décodage itératif pour les codes LDPC au-dela ̀ de la propagation de croyances. Shiva Planjery To cite this version: Shiva Planjery. Décodage itératif pour les codes LDPC au-dela ̀ de la propagation de croyances.. Théorie de l’information [cs.IT]. Universite ́ de Cergy Pontoise, 2012. Français. <tel-00819417>