期刊
IEEE TRANSACTIONS ON INFORMATION THEORY
卷 69, 期 2, 页码 910-927出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIT.2022.3206527
关键词
Decoding; Codes; DNA; Symbols; Encoding; Parity check codes; Convolutional codes; Achievable information rates; concatenated codes; DNA storage; insertion; deletion; substitution (IDS) channel; low-density parity-check (LDPC) code; polar code; synchronization codes
In this paper, two novel decoding algorithms are proposed for inferring the encoded sequences from multiple received sequences in DNA data storage systems. These algorithms significantly improve the decoding performance and optimize both the inner and outer coding schemes.
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 nonbinary low-density parity-check code or a polar code and either an inner convolutional code or a time-varying block code. We propose two novel 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 and has a complexity that is linear with the number of 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. In addition, we succeed in improving the performance of the aforementioned coding scheme by optimizing both the inner and outer codes.
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