Work

Robust error correction for real-valued signals via message-passing decoding and spatial coupling

Year: 2013

Type: conference-paper

Abstract: We revisit the error correction scheme of real-valued signals when the codeword is corrupted by gross errors on a fraction of entries and a small noise on all the entries. Combining the recent developments of approximate message passing and the spatially-coupled measurement matrix in compressed sensing we show that the error correction and its robustness towards noise can be enhanced considerably. We discuss the performance in the large signal limit using previous results on state evolution, as well as for finite size signals through numerical simulations. Even for relatively small sizes, the approach proposed here outperforms convex-relaxation-based decoders.

Source: IEEE Information Theory Workshop (ITW)

DOI: 10.1109/itw.2013.6691262

Authors: Jean Barbier, Florent Krzakala, Lenka Zdeborova, Pan Zhang

Institutions: Centre National de la Recherche Scientifique, Gulliver, Commissariat à l'Énergie Atomique et aux Énergies Alternatives, Institut de Physique Théorique

Language: English

Topic: Sparse and Compressive Sensing Techniques

Subfield: Computational Mechanics

Field: Engineering

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W2054945601

FWCI: 1.258

Cites: 22

Cited by: 7

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