13 research outputs found
Two-Bit Bit Flipping Decoding of LDPC Codes
In this paper, we propose a new class of bit flipping algorithms for
low-density parity-check (LDPC) codes over the binary symmetric channel (BSC).
Compared to the regular (parallel or serial) bit flipping algorithms, the
proposed algorithms employ one additional bit at a variable node to represent
its "strength." The introduction of this additional bit increases the
guaranteed error correction capability by a factor of at least 2. An additional
bit can also be employed at a check node to capture information which is
beneficial to decoding. A framework for failure analysis of the proposed
algorithms is described. These algorithms outperform the Gallager A/B algorithm
and the min-sum algorithm at much lower complexity. Concatenation of two-bit
bit flipping algorithms show a potential to approach the performance of belief
propagation (BP) decoding in the error floor region, also at lower complexity.Comment: 6 pages. Submitted to IEEE International Symposium on Information
Theory 201
Optimizing the Bit-flipping Method for Decoding Low-density Parity-check Codes in Wireless Networks by Using the Artificial Spider Algorithm
In this paper, the performance of Low-Density Parity-Check (LDPC) codes is improved, which leads to reduce the complexity of hard-decision Bit-Flipping (BF) decoding by utilizing the Artificial Spider Algorithm (ASA). The ASA is used to solve the optimization problem of decoding thresholds. Two decoding thresholds are used to flip multiple bits in each round of iteration to reduce the probability of errors and accelerate decoding convergence speed while improving decoding performance. These errors occur every time the bits are flipped. Then, the BF algorithm with a low-complexity optimizer only requires real number operations before iteration and logical operations in each iteration. The ASA is better than the optimized decoding scheme that uses the Particle Swarm Optimization (PSO) algorithm. The proposed scheme can improve the performance of wireless network applications with good proficiency and results. Simulation results show that the ASA-based algorithm for solving highly nonlinear unconstrained problems exhibits fast decoding convergence speed and excellent decoding performance. Thus, it is suitable for applications in broadband wireless networks
On Decoding Schemes for the MDPC-McEliece Cryptosystem
Recently, it has been shown how McEliece public-key cryptosystems based on
moderate-density parity-check (MDPC) codes allow for very compact keys compared
to variants based on other code families. In this paper, classical (iterative)
decoding schemes for MPDC codes are considered. The algorithms are analyzed
with respect to their error-correction capability as well as their resilience
against a recently proposed reaction-based key-recovery attack on a variant of
the MDPC-McEliece cryptosystem by Guo, Johansson and Stankovski (GJS). New
message-passing decoding algorithms are presented and analyzed. Two proposed
decoding algorithms have an improved error-correction performance compared to
existing hard-decision decoding schemes and are resilient against the GJS
reaction-based attack for an appropriate choice of the algorithm's parameters.
Finally, a modified belief propagation decoding algorithm that is resilient
against the GJS reaction-based attack is presented
On fuzzy syndrome hashing with LDPC coding
The last decades have seen a growing interest in hash functions that allow
some sort of tolerance, e.g. for the purpose of biometric authentication. Among
these, the syndrome fuzzy hashing construction allows to securely store
biometric data and to perform user authentication without the need of sharing
any secret key. This paper analyzes this model, showing that it offers a
suitable protection against information leakage and several advantages with
respect to similar solutions, such as the fuzzy commitment scheme. Furthermore,
the design and characterization of LDPC codes to be used for this purpose is
addressed.Comment: in Proceedings 4th International Symposium on Applied Sciences in
Biomedical and Communication Technologies (ISABEL), ACM 2011. This is the
author's version of the work. It is posted here by permission of ACM for your
personal use. Not for redistributio
Security and complexity of the McEliece cryptosystem based on QC-LDPC codes
In the context of public key cryptography, the McEliece cryptosystem
represents a very smart solution based on the hardness of the decoding problem,
which is believed to be able to resist the advent of quantum computers. Despite
this, the original McEliece cryptosystem, based on Goppa codes, has encountered
limited interest in practical applications, partly because of some constraints
imposed by this very special class of codes. We have recently introduced a
variant of the McEliece cryptosystem including low-density parity-check codes,
that are state-of-the-art codes, now used in many telecommunication standards
and applications. In this paper, we discuss the possible use of a bit-flipping
decoder in this context, which gives a significant advantage in terms of
complexity. We also provide theoretical arguments and practical tools for
estimating the trade-off between security and complexity, in such a way to give
a simple procedure for the system design.Comment: 22 pages, 1 figure. This paper is a preprint of a paper accepted by
IET Information Security and is subject to Institution of Engineering and
Technology Copyright. When the final version is published, the copy of record
will be available at IET Digital Librar
Noisy Gradient Descent Bit-Flip Decoding for LDPC Codes
A modified Gradient Descent Bit Flipping (GDBF) algorithm is proposed for
decoding Low Density Parity Check (LDPC) codes on the binary-input additive
white Gaussian noise channel. The new algorithm, called Noisy GDBF (NGDBF),
introduces a random perturbation into each symbol metric at each iteration. The
noise perturbation allows the algorithm to escape from undesirable local
maxima, resulting in improved performance. A combination of heuristic
improvements to the algorithm are proposed and evaluated. When the proposed
heuristics are applied, NGDBF performs better than any previously reported GDBF
variant, and comes within 0.5 dB of the belief propagation algorithm for
several tested codes. Unlike other previous GDBF algorithms that provide an
escape from local maxima, the proposed algorithm uses only local, fully
parallelizable operations and does not require computing a global objective
function or a sort over symbol metrics, making it highly efficient in
comparison. The proposed NGDBF algorithm requires channel state information
which must be obtained from a signal to noise ratio (SNR) estimator.
Architectural details are presented for implementing the NGDBF algorithm.
Complexity analysis and optimizations are also discussed.Comment: 16 pages, 22 figures, 2 table