Asymptotic Mutual Information Analysis for Double-scattering MIMO Channels: A New Approach by Gaussian Tools

TL;DR

This paper develops a Gaussian tools-based approach to analyze the asymptotic mutual information in double-scattering MIMO channels, providing convergence rates and insights into the effects of scatterers at high SNR.

Contribution

It introduces a new Gaussian tools method for deriving CLT and closed-form approximations for MI in double-scattering MIMO channels, with proven convergence rates.

Findings

Convergence rates of mean, variance, and characteristic function are O(1/N).

Impact of scatterer number on MI is analyzed at high SNR.

The framework applies to other double-scattering channel analyses.

Abstract

The asymptotic mutual information (MI) analysis for multiple-input multiple-output (MIMO) systems over double-scattering channels has achieved engaging results, but the convergence rates of the mean, variance, and the distribution of the MI are not yet available in the literature. In this paper, by utilizing the large random matrix theory (RMT), we give a central limit theory (CLT) for the MI and derive the closed-form approximation for the mean and the variance by a new approach -- Gaussian tools. The convergence rates of the mean, variance, and the characteristic function are proved to be O(1/N) for the first time, where N is the number of transmit antennas. Furthermore, the impact of the number of effective scatterers on the mean and variance was investigated in the moderate-to-high SNR regime with some interesting physical insights. The proposed evaluation framework can be utilized for the asymptotic performance analysis of other systems over double-scattering channels.