The use of multi-antenna arrays in both transmission and reception has been
shown to dramatically increase the throughput of wireless communication
systems. As a result there has been considerable interest in characterizing the
ergodic average of the mutual information for realistic correlated channels.
Here, an approach is presented that provides analytic expressions not only for
the average, but also the higher cumulant moments of the distribution of the
mutual information for zero-mean Gaussian (multiple-input multiple-output) MIMO
channels with the most general multipath covariance matrices when the channel
is known at the receiver. These channels include multi-tap delay paths, as well
as general channels with covariance matrices that cannot be written as a
Kronecker product, such as dual-polarized antenna arrays with general
correlations at both transmitter and receiver ends. The mathematical methods
are formally valid for large antenna numbers, in which limit it is shown that
all higher cumulant moments of the distribution, other than the first two scale
to zero. Thus, it is confirmed that the distribution of the mutual information
tends to a Gaussian, which enables one to calculate the outage capacity. These
results are quite accurate even in the case of a few antennas, which makes this
approach applicable to realistic situations.Comment: submitted for publication IEEE Trans. Information Theory; IEEEtran
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