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The case for structured random codes in network capacity theorems

Publications associées (38)

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Re-proving Channel Polarization Theorems

Mine Alsan

The general subject considered in this thesis is a recently discovered coding technique, polar coding, which is used to construct a class of error correction codes with unique properties. In his ground-breaking work, Arikan proved that this class of codes, ...

EPFL2015

Sparse Probabilistic Models

Andrei Giurgiu

This thesis is concerned with a number of novel uses of spatial coupling, applied to a class of probabilistic graphical models. These models include error correcting codes, random constraint satisfaction problems (CSPs) and statistical physics models calle ...

EPFL2015

Iterative Coding for Network Coding

Rüdiger Urbanke, Andrea Montanari

We consider communication over a noisy network under randomized linear network coding. Possible error mechanisms include node-or link-failures, Byzantine behavior of nodes, or an overestimate of the network min-cut. Building on the work of Kotter and Kschi ...

Ieee-Inst Electrical Electronics Engineers Inc2013

Scaling Exponent of List Decoders with Applications to Polar Codes

Rüdiger Urbanke, Seyed Hamed Hassani, Marco Mondelli

Motivated by the significant performance gains which polar codes experience when they are decoded with successive cancellation list decoders, we study how the scaling exponent changes as a function of the list size L. In particular, we fix the block error ...

Ieee2013

A Fast Hadamard Transform for Signals with Sub-linear Sparsity

Martin Vetterli, Robin Scheibler, Saeid Haghighatshoar

A new iterative low complexity algorithm has been presented for computing the Walsh-Hadamard transform (WHT) of an N dimensional signal with a K-sparse WHT, where N is a power of two and K = O(N^α), scales sub- linearly in N for some 0 < α < 1. Assuming a ...

2013

List-Decoding for the Arbitrarily Varying Channel Under State Constraints

Michael Christoph Gastpar

List-decoding for arbitrarily varying channels (AVCs) under state constraints is investigated. It is shown that rates within of the randomized coding capacity of AVCs with input-dependent state can be achieved under maximal error with list-decoding using l ...

2012

Rateless Codes for AVC Models

Michael Christoph Gastpar

The arbitrarily varying channel (AVC) is a channel model whose state is selected maliciously by an adversary. Fixed-blocklength coding assumes a worst-case bound on the adversary's capabilities, which leads to pessimistic results. This paper defines a vari ...

2010

Linear Universal Decoder for Compound Discrete Memoryless Channels

Rethnakaran Pulikkoonattu

Shannon in his seminal work \cite{paper:shannon} formalized the framework on the problem of digital communication of information and storage. He quantified the fundamental limits of compression and transmission rates. The quantity \textit{channel capacity} ...

2009

Capacity Achieving Codes from Randomness Conductors

Mahdi Cheraghchi Bashi Astaneh

We give a general framework for construction of small ensembles of capacity achieving linear codes for a wide range of (not necessarily memoryless) discrete symmetric channels, and in particular, the binary erasure and symmetric channels. The main tool use ...

2009

Statistical physics methods for sparse graph codes

Shrinivas Kudekar

This thesis deals with the asymptotic analysis of coding systems based on sparse graph codes. The goal of this work is to analyze the decoder performance when transmitting over a general binary-input memoryless symmetric-output (BMS) channel. We consider t ...

EPFL2009