Issue |
EPJ Web Conf.
Volume 226, 2020
Mathematical Modeling and Computational Physics 2019 (MMCP 2019)
|
|
---|---|---|
Article Number | 02006 | |
Number of page(s) | 4 | |
Section | Mathematical Modeling, Numerical Methods, and Simulation | |
DOI | https://doi.org/10.1051/epjconf/202022602006 | |
Published online | 20 January 2020 |
https://doi.org/10.1051/epjconf/202022602006
Genetic Optimization of LDPC Codes to Improve the Correction of Burst Errors
1
University of West Bohemia,
Pilsen,
Czech Republic
2
Institute of Technical and Experimantal Physics,
CTU in Prague,
Czech Republic
3
Yerevan State University,
Yerevan,
Armenia
4
A. I. Alikhanian National Laboratory (YerPhI),
Yerevan,
Armenia
5
Laboratory of Information Technologies, JINR,
Dubna,
Russia
Published online: 20 January 2020
Error correction plays a crucial role when transmitting data from the source to the destination through a noisy channel. It has found many applications in television broadcasting services, data transmission in radiation harsh environment (e. g. space probes or physical experiments) or memory storages influenced by Single Event Effects (SEE). Low Density Parity Check (LDPC) codes provide an important technique to correct these errors.
The parameters of error correction depend both on the decoding algorithm and on the LDPC code given by the parity-check matrix. Therefore, a particular design of the paritycheck matrix is necessary. Moreover, with the development of high performance computing, the application of genetic optimization algorithms to design the parity-check matrices has been enabled.
In this article, we present the application of the genetic optimization algorithm to produce error correcting codes with special properties, especially the burst types of errors. The results show the bounds of correction capabilities for various code lengths and various redundancies of LDPC codes. This is particularly useful when designing systems under the influence of noise combined with the application of the error correction codes.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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