Title :
SINR Statistics of Correlated MIMO Linear Receivers
Author :
Moustakas, Aris L. ; Kazakopoulos, Pavlos
Author_Institution :
Phys. Dept., Athens Univ., Athens, Greece
Abstract :
Linear receivers offer a low complexity option for multiantenna 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 deviation 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, to obtain 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 (2 × 2).
Keywords :
Gaussian channels; MIMO communication; antenna arrays; approximation theory; fading; mean square error methods; mobile communication; probability; Gaussian channel MIMO minimum mean square error; MMSE; SINR; SINR statistics; arbitrary transmission power profiles; correlated MIMO linear receivers; fading mobile environment; large deviation method; multiantenna communication systems; outage behavior; probability density; receiver antenna correlations; zero-forcing receivers; Antenna arrays; Interference; Receiving antennas; Signal to noise ratio; Transmitting antennas; Large deviations; minimum mean square error; multiple-input multiple-output (MIMO) channels; signal to noise ratio; zero forcing;
Journal_Title :
Information Theory, IEEE Transactions on
DOI :
10.1109/TIT.2013.2272034