Reconstruction from deletions in racetrack memories

Yeow Meng Chee, Ryan Gabrys, Alexander Vardy, Van Khu Vu, Eitan Yaakobi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this work, we study a special case of the reconstruction problem in order to combat position errors in racetrack memories. In these memories, the information is stored in magnetic cells that can be sensed by shifting them under read heads. However, since this shifting operation is not error free, recent work has been dedicated towards correcting these so-called position errors, which manifest themselves as deletions and sticky insertions. A deletion is the event where the cells are over-shifted, and a sticky insertion occurs when the cells are not shifted. We first present a code construction that uses two heads to correct two deletions with at most log2(log2 n) + 4 redundant bits. This result improves upon a recent one that requires roughly log2 n redundant bits. We then extend this construction to correct d deletions using d heads with at most log2(log2 n) + c redundant bits. Lastly, we extend our results and derive codes for the classical reconstruction problem by Levenshtein over the insertion/deletion channel.

Original languageEnglish
Title of host publication2018 IEEE Information Theory Workshop, ITW 2018
ISBN (Electronic)9781538635995
DOIs
StatePublished - 2 Jul 2018
Event2018 IEEE Information Theory Workshop, ITW 2018 - Guangzhou, China
Duration: 25 Nov 201829 Nov 2018

Publication series

Name2018 IEEE Information Theory Workshop, ITW 2018

Conference

Conference2018 IEEE Information Theory Workshop, ITW 2018
Country/TerritoryChina
CityGuangzhou
Period25/11/1829/11/18

All Science Journal Classification (ASJC) codes

  • Information Systems

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