Concatenated Codes for Recovery From Multiple Reads of DNA Sequences
Paper in 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

Technical University of Munich

Issam Maarouf

Simula UiB

Lorenz Welter

Technical University of Munich

Antonia Wachter-Zeh

Technical University of Munich

Eirik Rosnes

Simula UiB

Alexandre Graell I Amat

Simula UiB

Chalmers, Electrical Engineering, Communication and Antenna Systems, Communication Systems

2020 IEEE Information Theory Workshop (ITW)


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

Reliable and Secure Coded Edge Computing

Swedish Research Council (VR) (2020-03687), 2021-01-01 -- 2024-12-31.

Areas of Advance

Information and Communication Technology

Subject Categories


Communication Systems

Signal Processing



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