  Consider a fading Gaussian MIMO channel with $N_\mathrm{t}$ transmit and
$N_\mathrm{r}$ receive antennas. The transmitter selects $L_\mathrm{t}$
antennas corresponding to the strongest channels. For this setup, we study the
distribution of the input-output mutual information when $N_\mathrm{t}$ grows
large. We show that, for any $N_\mathrm{r}$ and $L_\mathrm{t}$, the
distribution of the input-output mutual information is accurately approximated
by a Gaussian distribution whose mean grows large and whose variance converges
to zero. Our analysis depicts that, in the large limit, the gap between the
expectation of the mutual information and its corresponding upper bound,
derived by applying Jensen's inequality, converges to a constant which only
depends on $N_\mathrm{r}$ and $L_\mathrm{t}$. The result extends the scope of
channel hardening to the general case of antenna selection with multiple
receive and selected transmit antennas. Although the analyses are given for the
large-system limit, our numerical investigations indicate the robustness of the
approximated distribution even when the number of antennas is not large.
