3,404 research outputs found
Modern Coding Theory: The Statistical Mechanics and Computer Science Point of View
These are the notes for a set of lectures delivered by the two authors at the
Les Houches Summer School on `Complex Systems' in July 2006. They provide an
introduction to the basic concepts in modern (probabilistic) coding theory,
highlighting connections with statistical mechanics. We also stress common
concepts with other disciplines dealing with similar problems that can be
generically referred to as `large graphical models'.
While most of the lectures are devoted to the classical channel coding
problem over simple memoryless channels, we present a discussion of more
complex channel models. We conclude with an overview of the main open
challenges in the field.Comment: Lectures at Les Houches Summer School on `Complex Systems', July
2006, 44 pages, 25 ps figure
Deterministic Constructions for Large Girth Protograph LDPC Codes
The bit-error threshold of the standard ensemble of Low Density Parity Check
(LDPC) codes is known to be close to capacity, if there is a non-zero fraction
of degree-two bit nodes. However, the degree-two bit nodes preclude the
possibility of a block-error threshold. Interestingly, LDPC codes constructed
using protographs allow the possibility of having both degree-two bit nodes and
a block-error threshold. In this paper, we analyze density evolution for
protograph LDPC codes over the binary erasure channel and show that their
bit-error probability decreases double exponentially with the number of
iterations when the erasure probability is below the bit-error threshold and
long chain of degree-two variable nodes are avoided in the protograph. We
present deterministic constructions of such protograph LDPC codes with girth
logarithmic in blocklength, resulting in an exponential fall in bit-error
probability below the threshold. We provide optimized protographs, whose
block-error thresholds are better than that of the standard ensemble with
minimum bit-node degree three. These protograph LDPC codes are theoretically of
great interest, and have applications, for instance, in coding with strong
secrecy over wiretap channels.Comment: 5 pages, 2 figures; To appear in ISIT 2013; Minor changes in
presentatio
Analysis of reaction and timing attacks against cryptosystems based on sparse parity-check codes
In this paper we study reaction and timing attacks against cryptosystems
based on sparse parity-check codes, which encompass low-density parity-check
(LDPC) codes and moderate-density parity-check (MDPC) codes. We show that the
feasibility of these attacks is not strictly associated to the quasi-cyclic
(QC) structure of the code but is related to the intrinsically probabilistic
decoding of any sparse parity-check code. So, these attacks not only work
against QC codes, but can be generalized to broader classes of codes. We
provide a novel algorithm that, in the case of a QC code, allows recovering a
larger amount of information than that retrievable through existing attacks and
we use this algorithm to characterize new side-channel information leakages. We
devise a theoretical model for the decoder that describes and justifies our
results. Numerical simulations are provided that confirm the effectiveness of
our approach
The Trapping Redundancy of Linear Block Codes
We generalize the notion of the stopping redundancy in order to study the
smallest size of a trapping set in Tanner graphs of linear block codes. In this
context, we introduce the notion of the trapping redundancy of a code, which
quantifies the relationship between the number of redundant rows in any
parity-check matrix of a given code and the size of its smallest trapping set.
Trapping sets with certain parameter sizes are known to cause error-floors in
the performance curves of iterative belief propagation decoders, and it is
therefore important to identify decoding matrices that avoid such sets. Bounds
on the trapping redundancy are obtained using probabilistic and constructive
methods, and the analysis covers both general and elementary trapping sets.
Numerical values for these bounds are computed for the [2640,1320] Margulis
code and the class of projective geometry codes, and compared with some new
code-specific trapping set size estimates.Comment: 12 pages, 4 tables, 1 figure, accepted for publication in IEEE
Transactions on Information Theor
Statistical mechanics of error exponents for error-correcting codes
Error exponents characterize the exponential decay, when increasing message
length, of the probability of error of many error-correcting codes. To tackle
the long standing problem of computing them exactly, we introduce a general,
thermodynamic, formalism that we illustrate with maximum-likelihood decoding of
low-density parity-check (LDPC) codes on the binary erasure channel (BEC) and
the binary symmetric channel (BSC). In this formalism, we apply the cavity
method for large deviations to derive expressions for both the average and
typical error exponents, which differ by the procedure used to select the codes
from specified ensembles. When decreasing the noise intensity, we find that two
phase transitions take place, at two different levels: a glass to ferromagnetic
transition in the space of codewords, and a paramagnetic to glass transition in
the space of codes.Comment: 32 pages, 13 figure
Sparse Graph Codes for Quantum Error-Correction
We present sparse graph codes appropriate for use in quantum
error-correction. Quantum error-correcting codes based on sparse graphs are of
interest for three reasons. First, the best codes currently known for classical
channels are based on sparse graphs. Second, sparse graph codes keep the number
of quantum interactions associated with the quantum error correction process
small: a constant number per quantum bit, independent of the blocklength.
Third, sparse graph codes often offer great flexibility with respect to
blocklength and rate. We believe some of the codes we present are unsurpassed
by previously published quantum error-correcting codes.Comment: Version 7.3e: 42 pages. Extended version, Feb 2004. A shortened
version was resubmitted to IEEE Transactions on Information Theory Jan 20,
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