A Deterministic Equivalent for the Analysis of Non-Gaussian Correlated MIMO Multiple Access Channels

TL;DR

This paper develops a deterministic equivalent approach for analyzing non-Gaussian correlated MIMO multiple access channels, enabling the use of Gaussian-based results to evaluate spectral efficiency in complex wireless systems.

Contribution

It introduces a method using the generalized Lindeberg principle to derive deterministic equivalents for non-Gaussian MIMO channels from Gaussian channel results.

Findings

Deterministic equivalents for non-Gaussian MIMO channels are derived.

The approach simplifies spectral efficiency analysis in complex MIMO systems.

Results are applicable to small cell networks with correlated channels.

Abstract

Large dimensional random matrix theory (RMT) has provided an efficient analytical tool to understand multiple-input multiple-output (MIMO) channels and to aid the design of MIMO wireless communication systems. However, previous studies based on large dimensional RMT rely on the assumption that the transmit correlation matrix is diagonal or the propagation channel matrix is Gaussian. There is an increasing interest in the channels where the transmit correlation matrices are generally nonnegative definite and the channel entries are non-Gaussian. This class of channel models appears in several applications in MIMO multiple access systems, such as small cell networks (SCNs). To address these problems, we use the generalized Lindeberg principle to show that the Stieltjes transforms of this class of random matrices with Gaussian or non-Gaussian independent entries coincide in the large dimensional regime. This result permits to derive the deterministic equivalents (e.g., the Stieltjes transform and the ergodic mutual information) for non-Gaussian MIMO channels from the known results developed for Gaussian MIMO channels, and is of great importance in characterizing the spectral efficiency of SCNs.