Layered Superposition Alphabet Enabling Binary Soft-Decision Decoding for Composite DNA Storage

Composite deoxyribonucleic acid storage represents information by nucleotide mixture ratios and can exceed 2 bits per synthesis cycle. Readout requires inferring the transmitted composite letter from finite sequencing counts subject to sampling randomness. For this purpose, we propose a layered one-hot superposition alphabet. Each layer maps a pair of coded bits from a binary component code to a one-hot nucleotide indicator, and a weighted sum of these indicators forms a composite letter. The layered structure supports multi-level coding and multi-stage decoding, allowing count-based likelihoods that account for finite sampling to be converted into soft inputs for binary component decoders. We use alphabet-constrained capacity to guide layer-weight selection and derive layer-wise capacities as references for component-code rate allocation. We also introduce a hard-decision-aided update that reduces marginalization over candidate layer combinations by fixing the nucleotide choices of previously decoded layers. Finite-length simulations with standardized low-density parity-check component codes from the Digital Video Broadcasting–Satellite–Second Generation standard demonstrate binary soft-decision decoding under finite sampling and substitution errors, and characterize the sequencing-depth requirements and sensitivity to mixture-ratio mismatch and oligo-wise coverage variation. Under symmetric substitution errors with probability 0.05, a four-layer design achieves 5.000 bits per synthesis cycle with a bit error rate below 10−4 at 57 reads per position.

Authors

Institutions

Publication Details

Journal
Entropy
Published
2026-10-30
DOI
https://doi.org/10.3390/e28111203
Primary Topic
DNA and Biological Computing
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Layered Superposition Alphabet Enabling Binary Soft-Decision Decoding for Composite DNA Storage

Ryo Shibata, Haruhiko Kaneko
3 links
Entropy
DNA and Biological Computing
article

Layered Superposition Alphabet Enabling Binary Soft-Decision Decoding for Composite DNA Storage

Ryo Shibata, Haruhiko Kaneko
article en

Abstract

Composite deoxyribonucleic acid storage represents information by nucleotide mixture ratios and can exceed 2 bits per synthesis cycle. Readout requires inferring the transmitted composite letter from finite sequencing counts subject to sampling randomness. For this purpose, we propose a layered one-hot superposition alphabet. Each layer maps a pair of coded bits from a binary component code to a one-hot nucleotide indicator, and a weighted sum of these indicators forms a composite letter. The layered structure supports multi-level coding and multi-stage decoding, allowing count-based likelihoods that account for finite sampling to be converted into soft inputs for binary component decoders. We use alphabet-constrained capacity to guide layer-weight selection and derive layer-wise capacities as references for component-code rate allocation. We also introduce a hard-decision-aided update that reduces marginalization over candidate layer combinations by fixing the nucleotide choices of previously decoded layers. Finite-length simulations with standardized low-density parity-check component codes from the Digital Video Broadcasting–Satellite–Second Generation standard demonstrate binary soft-decision decoding under finite sampling and substitution errors, and characterize the sequencing-depth requirements and sensitivity to mixture-ratio mismatch and oligo-wise coverage variation. Under symmetric substitution errors with probability 0.05, a four-layer design achieves 5.000 bits per synthesis cycle with a bit error rate below 10−4 at 57 reads per position.

EntropyVol. 28(11)
Shinshu University (JP), Institute of Science Tokyo (JP)
Japan Society for the Promotion of Science
Openalex Percentile: Top 22%
DNA and Biological Computing
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon