TY - GEN
T1 - Concatenated codes for recovery from multiple reads of DNA sequences
AU - Lenz, Andreas
AU - Maarouf, Issam
AU - Welter, Lorenz
AU - Wachter-Zeh, Antonia
AU - Rosnes, Eirik
AU - Graell i Amat, Alexandre
N1 - Publisher Copyright:
©2021 IEEE
PY - 2021/4/11
Y1 - 2021/4/11
N2 - Decoding sequences that stem from multiple transmissions of a codeword over an insertion, deletion, and substitution channel is a critical component of efficient deoxyribonucleic acid (DNA) data storage systems. In this paper, we consider a concatenated coding scheme with an outer low-density parity-check code and either an inner convolutional code or a block code. We propose two new decoding algorithms for inference from multiple received sequences, both combining the inner code and channel to a joint hidden Markov model to infer symbolwise a posteriori probabilities (APPs). The first decoder computes the exact APPs by jointly decoding the received sequences, whereas the second decoder approximates the APPs by combining the results of separately decoded received sequences. Using the proposed algorithms, we evaluate the performance of decoding multiple received sequences by means of achievable information rates and Monte-Carlo simulations. We show significant performance gains compared to a single received sequence.
AB - Decoding sequences that stem from multiple transmissions of a codeword over an insertion, deletion, and substitution channel is a critical component of efficient deoxyribonucleic acid (DNA) data storage systems. In this paper, we consider a concatenated coding scheme with an outer low-density parity-check code and either an inner convolutional code or a block code. We propose two new decoding algorithms for inference from multiple received sequences, both combining the inner code and channel to a joint hidden Markov model to infer symbolwise a posteriori probabilities (APPs). The first decoder computes the exact APPs by jointly decoding the received sequences, whereas the second decoder approximates the APPs by combining the results of separately decoded received sequences. Using the proposed algorithms, we evaluate the performance of decoding multiple received sequences by means of achievable information rates and Monte-Carlo simulations. We show significant performance gains compared to a single received sequence.
UR - http://www.scopus.com/inward/record.url?scp=85111185045&partnerID=8YFLogxK
U2 - 10.1109/ITW46852.2021.9457675
DO - 10.1109/ITW46852.2021.9457675
M3 - Conference contribution
AN - SCOPUS:85111185045
T3 - 2020 IEEE Information Theory Workshop, ITW 2020
BT - 2020 IEEE Information Theory Workshop, ITW 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE Information Theory Workshop, ITW 2020
Y2 - 11 April 2021 through 15 April 2021
ER -