Achievable Information Rates and Concatenated Codes for the DNA Nanopore Sequencing Channel

The errors occurring in DNA-based storage are correlated in nature, which is a direct consequence of the synthesis and sequencing processes. In this paper, we consider the memory-$k$ nanopore channel model recently introduced by Hamoum et al., which models the inherent memory of the channel. We derive the maximum a posteriori (MAP) decoder for this channel model. The derived MAP decoder allows us to compute achievable information rates for the true DNA storage channel assuming a mismatched decoder matched to the memory-$k$ nanopore channel model, and quantify the loss in performance assuming a small memory length--and hence limited decoding complexity. Furthermore, the derived MAP decoder can be used to design error-correcting codes tailored to the DNA storage channel. We show that a concatenated coding scheme with an outer low-density parity-check code and an inner convolutional code yields excellent performance.Comment: This paper has been accepted and awaiting publication in informatio theory workshop (ITW) 202

On capacity and coding for segmented deletion channels

We consider binary deletion channels with a segmentation assumption which appears to be suited for more practical scenarios. Unlike the binary independent and identically distributed (i.i.d.) deletion channel where each bit is independently deleted with an equal probability, the segmentation assumption prohibits certain transmitted bits to be deleted, i.e., in a block of bits of a certain length, only a limited number of deletions can occur. We first propose several upper and lower capacity bounds for the segmented deletion channel. Then we focus on an interleaved concatenation of an outer low-density parity check (LDPC) code with error-correction capabilities and an inner marker code with synchronization capabilities over these channels. With the help of a specifically designed maximum-a-posteriori (MAP) detector, we demonstrate reliable transmission at higher code rates than the existing ones reported in the literature. © 2011 IEEE

Capacity Bounds and Concatenated Codes Over Segmented Deletion Channels

Cataloged from PDF version of article.We develop an information theoretic characterization and a practical coding approach for segmented deletion channels. Compared to channels with independent and identically distributed (i.i.d.) deletions, where each bit is independently deleted with an equal probability, the segmentation assumption imposes certain constraints, i.e., in a block of bits of a certain length, only a limited number of deletions are allowed to occur. This channel model has recently been proposed and motivated by the fact that for practical systems, when a deletion error occurs, it is more likely that the next one will not appear very soon. We first argue that such channels are information stable, hence their channel capacity exists. Then, we introduce several upper and lower bounds with two different methods in an attempt to understand the channel capacity behavior. The first scheme utilizes certain information provided to the transmitter and/or receiver while the second one explores the asymptotic behavior of the bounds when the average bit deletion rate is small. In the second part of the paper, we consider a practical channel coding approach over a segmented deletion channel. Specifically, we utilize outer LDPC codes concatenated with inner marker codes, and develop suitable channel detection algorithms for this scenario. Different maximum-a-posteriori (MAP) based channel synchronization algorithms operating at the bit and symbol levels are introduced, and specific LDPC code designs are explored. Simulation results clearly indicate the advantages of the proposed approach. In particular, for the entire range of deletion probabilities less than unity, our scheme offers a significantly larger transmission rate compared to the other existing solutions in the literature

Capacity bounds and concatenated codes over segmented deletion channels

We develop an information theoretic characterization and a practical coding approach for segmented deletion channels. Compared to channels with independent and identically distributed (i.i.d.) deletions, where each bit is independently deleted with an equal probability, the segmentation assumption imposes certain constraints, i.e., in a block of bits of a certain length, only a limited number of deletions are allowed to occur. This channel model has recently been proposed and motivated by the fact that for practical systems, when a deletion error occurs, it is more likely that the next one will not appear very soon. We first argue that such channels are information stable, hence their channel capacity exists. Then, we introduce several upper and lower bounds with two different methods in an attempt to understand the channel capacity behavior. The first scheme utilizes certain information provided to the transmitter and/or receiver while the second one explores the asymptotic behavior of the bounds when the average bit deletion rate is small. In the second part of the paper, we consider a practical channel coding approach over a segmented deletion channel. Specifically, we utilize outer LDPC codes concatenated with inner marker codes, and develop suitable channel detection algorithms for this scenario. Different maximum-a-posteriori (MAP) based channel synchronization algorithms operating at the bit and symbol levels are introduced, and specific LDPC code designs are explored. Simulation results clearly indicate the advantages of the proposed approach. In particular, for the entire range of deletion probabilities less than unity, our scheme offers a significantly larger transmission rate compared to the other existing solutions in the literature. © 1972-2012 IEEE

Incorporating pitch features for tone modeling in automatic recognition of Mandarin Chinese

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.Cataloged from PDF version of thesis.Includes bibliographical references (p. 53-56).Tone plays a fundamental role in Mandarin Chinese, as it plays a lexical role in determining the meanings of words in spoken Mandarin. For example, these two sentences ... (I like horses) and ... (I like to scold) differ only in the tone carried by the last syllable. Thus, the inclusion of tone-related information through analysis of pitch data should improve the performance of automatic speech recognition (ASR) systems on Mandarin Chinese. The focus of this thesis is to improve the performance of a non-tonal automatic speech recognition (ASR) system on a Mandarin Chinese corpus by implementing modifications to the system code to incorporate pitch features. We compile and format a Mandarin Chinese broadcast new corpus for use with the ASR system, and implement a pitch feature extraction algorithm. Additionally, we investigate two algorithms for incorporating pitch features in Mandarin Chinese speech recognition. Firstly, we build and test a baseline tonal ASR system with embedded tone modeling by concatenating the cepstral and pitch feature vectors for use as the input to our phonetic model (a Hidden Markov Model, or HMM). We find that our embedded tone modeling algorithm does improve performance on Mandarin Chinese, showing that including tonal information is in fact contributive for Mandarin Chinese speech recognition. Secondly, we implement and test the effectiveness of HMM-based multistream models.by Karen Lingyun Chu.M.Eng