On the Smallest Eigenvalue of General correlated Gaussian Matrices

Abstract

This paper investigates the behaviour of the spectrum of generally correlated Gaussian random matrices whose columns are zero-mean independent vectors but have different correlations, under the specific regime where the number of their columns and that of their rows grow at infinity with the same pace. This work is, in particular, motivated by applications from statistical signal processing and wireless communications, where this kind of matrices naturally arise. Following the approach proposed in [1], we prove that under some specific conditions, the smallest singular value of generally correlated Gaussian matrices is almost surely away from zero.

References in corpus (2)

• Linear Precoding Based on Polynomial Expansion: Large-Scale Multi-Cell MIMO Systems
• A New Approach for Capacity Analysis of Large Dimensional Multi-Antenna Channels