2020 IEEE International Symposium
on Information Theory
21-26 June 2020 • Los Angeles, California, USA
| Paper ID | M.8.6 | ||
| Paper Title | Symbolwise MAP Estimation for Multiple-Trace Insertion/Deletion/Substitution Channels | ||
| Authors | Ryo Sakogawa, Haruhiko Kaneko, Tokyo Institute of Technology, Japan | ||
| Session | M.8: Insertion Deletion Substitution Codes II | ||
| Presentation | Lecture | ||
| Track | Coding for Storage and Memories | ||
| Manuscript | Click here to download the manuscript | ||
| Virtual Presentation | Click here to watch in the Virtual Symposium | ||
| Abstract | In this paper, we work on the symbolwise maximum a posteriori probability (MAP) estimation of channel input symbol from $m$ $(\geq 2)$ received words (traces) having insertion/deletion/substitution (IDS) errors, where the errors are independent between $m$ received words. This problem is motivated by readout process in next-generation sequencers of DNA storage. The MAP estimation is based on the belief propagation algorithm on a factor graph, which represents the joint probability of a channel input word and $m$ pairs of channel output word and drift vector. We also propose a heuristic estimation algorithm for $m \geq 4$ to reduce the computational complexity. Simulation results show the relation between channel IDS error rate and estimation error rate. | ||
Plan Ahead
2021 IEEE International Symposium on Information Theory
11-16 July 2021 | Melbourne, Victoria, Australia
