Capacity Region of the Gaussian Arbitrarily-Varying Broadcast Channel

Fatemeh Hosseinigoki, Oliver Kosut

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


This paper considers the two-user Gaussian arbitrarily-varying broadcast channel, wherein a power-limited transmitter wishes to send a message to each of two receivers. Each receiver sees a superposition of the transmitter's sequence, Gaussian noise, and a signal from a power-limited malicious jammer. The jammer is assumed to know the code, but is oblivious to real-time transmissions. The exact capacity region of this setting is determined to be the capacity region of the standard Gaussian broadcast channel, but with the noise variance increased by the power of the jammer, as long as the received power of the jammer at each receiver is less than that of the legitimate transmitter. A key aspect of the achievable scheme involves sharing randomness from the transmitter to the receivers by breaking the transmitted sequence into segments, and either transmitting at full power in a segment, or sending zero. By coding over the on/off signal, a small shared randomness can be established without corruption by the jammer, and without interfering with the standard superposition coding strategy for the Gaussian broadcast channel.

Original languageEnglish (US)
Title of host publication2020 IEEE International Symposium on Information Theory, ISIT 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages5
ISBN (Electronic)9781728164328
StatePublished - Jun 2020
Event2020 IEEE International Symposium on Information Theory, ISIT 2020 - Los Angeles, United States
Duration: Jul 21 2020Jul 26 2020

Publication series

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


Conference2020 IEEE International Symposium on Information Theory, ISIT 2020
Country/TerritoryUnited States
CityLos Angeles

ASJC Scopus subject areas

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


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