Minimax Bounds for Blind Network Inference

Nishant Mehrotra, Eric Graves, Ananthram Swami, Ashutosh Sabharwal

Research output: Chapter in Book/Report/Conference proceedingConference contribution


We take the first step towards understanding the fundamental limits of blind wireless network inference performed by a distributed network of single-antenna adversary nodes. The distributed adversary nodes are assumed to be blind to the protocol parameters as well as the modulation, coding and encryption schemes used by the network being monitored. Focusing on the special case of inferring the channel access probabilities of the monitored nodes, we derive minimax bounds for blind inference. We show that blind inference is possible with similar sample complexity (asymptotically) as non-blind inference given certain network connectivity conditions are satisfied.

Original languageEnglish (US)
Title of host publication2021 IEEE International Symposium on Information Theory, ISIT 2021 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9781538682098
StatePublished - Jul 12 2021
Event2021 IEEE International Symposium on Information Theory, ISIT 2021 - Virtual, Melbourne, Australia
Duration: Jul 12 2021Jul 20 2021

Publication series

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


Conference2021 IEEE International Symposium on Information Theory, ISIT 2021
CityVirtual, Melbourne

ASJC Scopus subject areas

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


Dive into the research topics of 'Minimax Bounds for Blind Network Inference'. Together they form a unique fingerprint.

Cite this