Performance of mutual information inference methods under unknown interference

TL;DR

This paper introduces a new G-estimator for mutual information in MIMO channels with unknown interference, demonstrating its consistency and asymptotic Gaussian behavior through theoretical analysis and simulations.

Contribution

A novel G-estimator for mutual information under unknown interference, with proven consistency and asymptotic normality in large-dimensional regimes.

Findings

G-estimator is consistent as antennas and observations increase

The estimator satisfies a central limit theorem with Gaussian fluctuations

Simulations confirm theoretical results even for small systems

Abstract

The problem of fast point-to-point MIMO 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 {\em 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.