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Erasure Schemes Using Generalized Polar Codes: Zero-Undetected-Error Capacity and Performance Trade-offs

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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

Polar Codes: Finite Length Implementation, Error Correlations and Multilevel Modulation

Shannon, in his seminal work, formalized the transmission of data over a communication channel and determined its fundamental limits. He characterized the relation between communication rate and error probability and showed that as long as the communicatio ...

2012

Analysis of the Second Moment of the LT Decoder

Mohammad Amin Shokrollahi, Ghid Maatouk

In this paper, the second moment of the ripple size during the Luby transform (LT) decoding process is analyzed. Combined with a result by Karp et al. (2004) stating that the expectation of the ripple size is of the order of k, our study gives bounds on th ...

2012

Threshold Saturation via Spatial Coupling: Why Convolutional LDPC Ensembles Perform So Well over the BEC

Rüdiger Urbanke, Shrinivas Kudekar

Convolutional low-density parity-check (LDPC) ensembles, introduced by Felstrom and Zigangirov, have excellent thresholds and these thresholds are rapidly increasing functions of the average degree. Several variations on the basic theme have been proposed ...

2011

Phase Transitions for Mutual Information

Mohammad Amin Shokrollahi, Krishna Kumar, Amir Hesam Salavati, Raj Kumar Krishna Kumar

We consider ensembles of binary linear error correcting codes, obtained by sampling each column of the generator matrix G or parity check matrix H independently from the set of all binary vectors of weight d (of appropriate dimension). We investigate the c ...

IEEE2010

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

Polar codes for channel and source coding

Satish Babu Korada

The two central topics of information theory are the compression and the transmission of data. Shannon, in his seminal work, formalized both these problems and determined their fundamental limits. Since then the main goal of coding theory has been to find ...

EPFL2009

Source and channel coding using Fountain codes

Bertrand Ndzana Ndzana

The invention of Fountain codes is a major advance in the field of error correcting codes. The goal of this work is to study and develop algorithms for source and channel coding using a family of Fountain codes known as Raptor codes. From an asymptotic poi ...

EPFL2009

Concentration of Magnetization for Linear Block Codes

Nicolas Macris, Satish Babu Korada, Shrinivas Kudekar

We consider communication over the binary erasure and the binary additive white gaussian noise channels using fixed linear block codes and also appropriate ensembles of such codes. We show concentration of the magnetization over the channel realizations an ...

2008

Finite-length scaling of repeat-accumulate codes on the BEC

In this paper we consider the finite-length performance of Repeat-Accumulate codes in the waterfall region assuming the transmission on the binary erasure channel. We extend the finite-length scaling law of LDPC codes [1] to this ensemble and we derive the ...

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