SINR Statistics of Correlated MIMO Linear Receivers

TL;DR

This paper develops a large deviations method to accurately characterize the SINR distribution for correlated MIMO linear receivers, including tail behaviors, with applications to outage probability and bit-error-rate.

Contribution

It introduces a novel large deviations approach for SINR distribution in correlated MIMO systems, extending Gaussian approximations to include non-Gaussian tails.

Findings

Accurate SINR distribution including tails for small and large antenna arrays.

Analytical expressions for outage probability and bit-error-rate.

Method outperforms existing Gaussian and Gamma approximations.

Abstract

Linear receivers offer a low complexity option for multi-antenna communication systems. Therefore, understanding the outage behavior of the corresponding SINR is important in a fading mobile environment. In this paper we introduce a large deviations method, valid nominally for a large number M of antennas, which provides the probability density of the SINR of Gaussian channel MIMO Minimum Mean Square Error (MMSE) and zero-forcing (ZF) receivers, with arbitrary transmission power profiles and in the presence of receiver antenna correlations. This approach extends the Gaussian approximation of the SINR, valid for large M asymptotically close to the center of the distribution, obtaining the non-Gaussian tails of the distribution. Our methodology allows us to calculate the SINR distribution to next-to-leading order (O(1/M)) and showcase the deviations from approximations that have appeared in the literature (e.g. the Gaussian or the generalized Gamma distribution). We also analytically evaluate the outage probability, as well as the uncoded bit-error-rate. We find that our approximation is quite accurate even for the smallest antenna arrays (2x2).