MIMO Interference Alignment Over Correlated Channels with Imperfect CSI

TL;DR

This paper derives an approximate SINR expression for MIMO interference alignment with imperfect CSI and antenna correlation, enabling performance analysis and comparison with other transmission methods.

Contribution

It provides a novel closed-form SINR approximation for IA under realistic conditions like imperfect CSI and antenna correlation, using random matrix theory.

Findings

IA's performance can be accurately predicted with the derived SINR expression.

IA may not always outperform spatial multiplexing and beamforming.

The analysis facilitates realistic performance comparisons of IA in practical scenarios.

Abstract

Interference alignment (IA), given uncorrelated channel components and perfect channel state information, obtains the maximum degrees of freedom in an interference channel. Little is known, however, about how the sum rate of IA behaves at finite transmit power, with imperfect channel state information, or antenna correlation. This paper provides an approximate closed-form signal-to-interference-plus-noise-ratio (SINR) expression for IA over multiple-input-multiple-output (MIMO) channels with imperfect channel state information and transmit antenna correlation. Assuming linear processing at the transmitters and zero-forcing receivers, random matrix theory tools are utilized to derive an approximation for the post-processing SINR distribution of each stream for each user. Perfect channel knowledge and i.i.d. channel coefficients constitute special cases. This SINR distribution not only allows easy calculation of useful performance metrics like sum rate and symbol error rate, but also permits a realistic comparison of IA with other transmission techniques. More specifically, IA is compared with spatial multiplexing and beamforming and it is shown that IA may not be optimal for some performance criteria.