No eigenvalues outside the support of the limiting empirical spectral distribution of a separable covariance matrix

We consider a class of matrices of the form C"n=(1/N)A"n^1^/^2X"nB"nX"n^*xA"n^1^/^2, where X"n is an nxN matrix consisting of i.i.d. standardized complex entries, A"n^1^/^2 is a nonnegative definite square root of the nonnegative definite Hermitian matrix A"n, and B"n is diagonal with nonnegative diagonal entries. Under the assumption that the distributions of the eigenvalues of A"n and B"n converge to proper probability distributions as nN->[email protected]?(0,~), the empirical spectral distribution of C"n converges a.s. to a non-random limit. We show that, under appropriate conditions on the eigenvalues of A"n and B"n, with probability 1, there will be no eigenvalues in any closed interval outside the support of the limiting distribution, for sufficiently large n. The problem is motivated by applications in spatio-temporal statistics and wireless communications.