The Bee-Identification Error Exponent with Absentee Bees

Anshoo Tandon, Vincent Y.F. Tan, Lav R. Varshney

Research output: Contribution to journalArticlepeer-review

Abstract

The 'bee-identification problem' was formally defined by Tandon, Tan and Varshney [IEEE Trans. Commun., vol. 67, 2019], and the error exponent was studied. This work extends the results for the 'absentee bees' scenario, where a fraction of the bees are absent in the beehive image used for identification. For this setting, we present an exact characterization of the bee-identification error exponent, and show that independent barcode decoding is optimal, i.e., joint decoding of the bee barcodes does not result in a better error exponent relative to independent decoding of each noisy barcode. This is in contrast to the result without absentee bees, where joint barcode decoding results in a significantly higher error exponent than independent barcode decoding. We also define and characterize the 'capacity' for the bee-identification problem with absentee bees, and prove a strong converse for the same.

Original languageEnglish (US)
Article number9177080
Pages (from-to)7602-7614
Number of pages13
JournalIEEE Transactions on Information Theory
Volume66
Issue number12
DOIs
StatePublished - Dec 2020

Keywords

  • Bee-identification problem
  • absentee bees
  • capacity
  • error exponent
  • noisy channel
  • strong converse

ASJC Scopus subject areas

  • Information Systems
  • Computer Science Applications
  • Library and Information Sciences

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