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. 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.
翻译:插入、 删除和替换通道的编码多次传输产生的解码序列,是高效脱氧核糖核酸(DNA)数据储存系统的关键组成部分。 在本文中,我们考虑的是外非二元低密度对等检查代码或极代代码的混合编码办法,以及内部共变代码或时间变化区块代码。我们提议了两种新型解码算法,用以推断从多个收到序列中得出的解码序列,两者结合了内部编码和连接到一个联合隐藏的Markov模型的渠道,以推断出后继概率(APPs)的符号。第一个解码器通过联合解码收到的序列来计算准确的APs,而第二个解码器则通过合并分别解码收到序列的结果来接近APs。我们使用拟议的算法,通过可实现的信息率和蒙特-卡洛模拟来评估解码多重收到序列的性能。我们展示了与单一收到序列相比的显著性能收益。此外,我们通过优化内部代码和内部代码,从而改进了上述两部的绩效。