Concatenated Codes for Recovery From Multiple Reads of DNA Sequences
Paper i proceeding, 2021

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.


Andreas Lenz

Technische Universität München

Issam Maarouf

Simula UiB

Lorenz Welter

Technische Universität München

Antonia Wachter-Zeh

Technische Universität München

Eirik Rosnes

Simula UiB

Alexandre Graell I Amat

Simula UiB

Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk

2020 IEEE Information Theory Workshop, ITW 2020

9781728159621 (ISBN)

IEEE Information Theory Workshop (ITW). (Invited paper)
Riva del Garda, Italy,

Pålitlig och säker kodad kantberäkning

Vetenskapsrådet (VR) (2020-03687), 2021-01-01 -- 2024-12-31.


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