Using a large deviations approach we calculate the probability distribution
of the mutual information of MIMO channels in the limit of large antenna
numbers. In contrast to previous methods that only focused at the distribution
close to its mean (thus obtaining an asymptotically Gaussian distribution), we
calculate the full distribution, including its tails which strongly deviate
from the Gaussian behavior near the mean. The resulting distribution
interpolates seamlessly between the Gaussian approximation for rates R close
to the ergodic value of the mutual information and the approach of Zheng and
Tse for large signal to noise ratios ρ. This calculation provides us with
a tool to obtain outage probabilities analytically at any point in the (R,ρ,N) parameter space, as long as the number of antennas N is not too
small. In addition, this method also yields the probability distribution of
eigenvalues constrained in the subspace where the mutual information per
antenna is fixed to R for a given ρ. Quite remarkably, this eigenvalue
density is of the form of the Marcenko-Pastur distribution with square-root
singularities, and it depends on the values of R and ρ.Comment: Accepted for publication, IEEE Transactions on Information Theory
(2010). Part of this work appears in the Proc. IEEE Information Theory
Workshop, June 2009, Volos, Greec