An Asymmetric-Error-Aware LDPC Decoding Algorithm for DNA Storage

With the rapid growth of data, DNA is attracting attention as a promising storage medium due to its durability, large storage capacity, and high bulk density. However, errors occur in DNA synthesis and sequencing processes, with substitutions being the most common errors in DNA storage process. To a...

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Vydané v:IEEE communications letters Ročník 27; číslo 1; s. 1
Hlavní autori: Sun, Yi, Han, Guojun, Liu, Chang, Wang, Yixin, Fang, Yi
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York IEEE 01.01.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Algorithms
asymmetric substitutions
Asymmetry
belief-propagation (BP) decoding
Bit error rate
bit error rate reduction
Bulk density
Codes
Data storage
Decoding
DNA
DNA data storage
Error correcting codes
Error correction
Error reduction
Gene sequencing
Iterative decoding
Likelihood ratio
low-density parity-check (LDPC) codes
Memory
Nucleotides
Sequential analysis
Storage capacity
Symbols
ISSN:1089-7798, 1558-2558
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Shrnutí:With the rapid growth of data, DNA is attracting attention as a promising storage medium due to its durability, large storage capacity, and high bulk density. However, errors occur in DNA synthesis and sequencing processes, with substitutions being the most common errors in DNA storage process. To address this issue, we select low-density parity-check (LDPC) codes as the error correction method to guarantee data reliability. However, unlike traditional data storage channels, errors occurring between nucleotides in the DNA channel are asymmetric. Therefore, traditional belief propagation (BP) decoding algorithm is not sufficient for effective error correction under DNA channel. In this letter, we propose to use two LDPC codes and take error types as additional information for calibrating log-likelihood ratio (LLR) value. In addition, compared with previous works, simulation results show that our proposed decoding algorithm can reduce bit error rate (BER) by 33% ~ 94%.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1089-7798
1558-2558
DOI:10.1109/LCOMM.2022.3216408