Publications de Vahid Aref | EPFL Graph Search

A Compressed Sensing Approach for Distribution Matching

In this work, we formulate the fixed-length distribution matching as a Bayesian inference problem. Our proposed solution is inspired from the compressed sensing paradigm and the sparse superposition (SS) codes. First, we introduce sparsity in the binary so ...

IEEE2018

Approaching the Rate-Distortion Limit With Spatial Coupling, Belief Propagation, and Decimation

Nicolas Macris, Vahid Aref, Marc Vuffray

We investigate an encoding scheme for lossy compression of a binary symmetric source based on simple spatially coupled low-density generator-matrix codes. The degree of the check nodes is regular and the one of code-bits is Poisson distributed with an aver ...

Institute of Electrical and Electronics Engineers2015

Spatially Coupled Codes for Channel and Source Coding

Vahid Aref

EPFL2014

Approaching the Rate-Distortion Limit by spatial Coupling with Belief Propagation and Decimation

Nicolas Macris, Vahid Aref, Marc Vuffray

We investigate an encoding scheme for lossy compression based on spatially coupled Low-Density Generator-Matrix codes. The degree distributions are regular, or are Poisson on the code-bit side and check-regular which allows use for any compression rate. Th ...

2013

On the Convergence Speed of Spatially Coupled LDPC Ensembles

Vahid Aref

Spatially coupled low-density parity-check codes show an outstanding performance under the low-complexity belief propagation (BP) decoding algorithm. They exhibit a peculiar convergence phenomenon above the BP threshold of the underlying non-coupled ensemb ...

2013

Lossy source coding via spatially coupled LDGM ensembles

Rüdiger Urbanke, Nicolas Macris, Vahid Aref, Marc Vuffray

We study a new encoding scheme for lossy source compression based on spatially coupled low-density generatormatrix codes. We develop a belief-propagation guided-decimation algorithm, and show that this algorithm allows to approach the optimal distortion of ...

Ieee2012