List-decoding capacity of the Gaussian arbitrarily-varying channel

Fatemeh Hosseinigoki, Oliver Kosut

Research output: Contribution to journalArticle

Abstract

In this paper, we determine the capacity of the Gaussian arbitrarily-varying channel with a (possibly stochastic) encoder and a deterministic list-decoder under the average probability of error criterion. We assume that both the legitimate and the adversarial signals are restricted by their power constraints. We also assume that there is no path between the adversary and the legitimate user but the adversary knows the legitimate user's code. We show that for any list size L, the capacity is equivalent to the capacity of a point-to-point Gaussian channel with noise variance increased by the adversary power, if the adversary has less power than L times the transmitter power; otherwise, the capacity is zero. In the converse proof, we show that if the adversary has enough power, then the decoder can be confounded by the adversarial superposition of several codewords while satisfying its power constraint with positive probability. The achievability proof benefits from a novel variant of the Csiszár-Narayan method for the arbitrarily-varying channel.

Original languageEnglish (US)
Article number575
JournalEntropy
Volume21
Issue number6
DOIs
StatePublished - Jun 1 2019

Keywords

  • Capacity
  • Gaussian arbitrarily-varying channel
  • List-decoding
  • Stochastic encoder

ASJC Scopus subject areas

  • Physics and Astronomy(all)

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