Codes Over Absorption Channels

Zuo Ye, Ohad Elishco

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


In this paper, we present a novel communication channel, called the absorption channel, inspired by information transmission in neurons. Our motivation comes from invivo nano-machines, emerging medical applications, and brain-machine interfaces that communicate over the nervous system.For any given finite alphabet, we give codes that can correct absorption errors. For the binary alphabet, the known binary (multiple-)deletion correcting codes already provide a good solution. For single-absorption error, we prove that the Varshamov-Tenengolts codes can provide a near-optimal code in our setting. When the alphabet size q is at least 3, we first construct a single-absorption correcting code whose redundancy is at most 3 logq (n)+O(1). Then, based on this code and ideas introduced in [1], we give a second construction of single-absorption correcting codes with redundancy logq(n) + 12 logq logq(n) + O(1), which is optimal up to an O(logq logq(n)).Finally, we apply the syndrome compression technique with pre-coding to obtain a subcode of the single-absorption correcting code. This subcode can combat multiple-absorption errors and has low redundancy.

Original languageEnglish
Title of host publication2023 IEEE International Symposium on Information Theory, ISIT 2023
PublisherInstitute of Electrical and Electronics Engineers
Number of pages6
ISBN (Electronic)9781665475549
StatePublished - 1 Jan 2023
Event2023 IEEE International Symposium on Information Theory, ISIT 2023 - Taipei, Taiwan, Province of China
Duration: 25 Jun 202330 Jun 2023

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
ISSN (Print)2157-8095


Conference2023 IEEE International Symposium on Information Theory, ISIT 2023
Country/TerritoryTaiwan, Province of China

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Information Systems
  • Modeling and Simulation
  • Applied Mathematics


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