Asymptotic Analysis of Double-Scattering Channels

TL;DR

This paper uses random matrix theory to derive deterministic approximations for key performance metrics in MIMO double-scattering channels, providing insights into system capacity and optimal transmission strategies.

Contribution

It introduces novel asymptotic analysis techniques for double-scattering MIMO channels, including deterministic approximations and optimal covariance matrices.

Findings

Deterministic approximations are accurate for realistic system sizes.

Derived asymptotically optimal transmit covariance matrices.

Analysis improves understanding of MIMO double-scattering channel capacity.

Abstract

We consider a multiple-input multiple-output (MIMO) multiple access channel (MAC), where the channel between each transmitter and the receiver is modeled by the doubly-scattering channel model. Based on novel techniques from random matrix theory, we derive deterministic approximations of the mutual information, the signal-to-noise-plus-interference-ratio (SINR) at the output of the minimum-mean-square-error (MMSE) detector and the sum-rate with MMSE detection which are almost surely tight in the large system limit. Moreover, we derive the asymptotically optimal transmit covariance matrices. Our simulation results show that the asymptotic analysis provides very close approximations for realistic system dimensions.