Performance of mutual information inference methods under unknown interference

Abla Kammoun*, Romain Couillet, Jamal Najim, Mérouane Debbah

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


In this paper, the problem of fast point-to-point multiple-input-multiple- output channel mutual information estimation is addressed, in the situation where the receiver undergoes unknown colored interference, whereas the channel with the transmitter is perfectly known. The considered scenario assumes that the estimation is based on a few channel use observations during a short sensing period. Using large dimensional random matrix theory, an estimator referred to as G-estimator is derived. This estimator is proved to be consistent as the number of antennas and observations grow large and its asymptotic performance is analyzed. In particular, the G-estimator satisfies a central limit theorem with asymptotic Gaussian fluctuations. Simulations are provided which strongly support the theoretical results, even for small system dimensions.

Original languageEnglish (US)
Article number6303912
Pages (from-to)1129-1148
Number of pages20
JournalIEEE Transactions on Information Theory
Issue number2
StatePublished - 2013
Externally publishedYes


  • Central limit theorem
  • G-estimation
  • mutual information inference
  • random matrices

ASJC Scopus subject areas

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


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