In this paper we consider point-to-point multiantenna channels with certain
block distributional symmetries which do not require the entries of the channel
matrix to be either Gaussian, or independent, or identically distributed. A
main contribution is a capacity theorem for these channels, which might be
regarded as a generalization of Telatar's theorem (1999), which reduces the
numerical optimization domain in the capacity computation. With this
information theoretic result and some free probability arguments, we prove an
asymptotic capacity theorem that, in addition to reducing the optimization
domain, does not depend on the dimension of the channel matrix. This theorem
allows us to apply free probability techniques to numerically compute the
asymptotic capacity of the channels under consideration. These theorems provide
a very efficient method for numerically approximating both the capacity and a
capacity achieving input covariance matrix of certain channels.Comment: Accepted for publication in the IEEE Transactions on Information
Theory; 13 page