  Densifying the network and deploying more antennas at each access point are
two principal ways to boost the capacity of wireless networks. However, due to
the complicated distributions of random signal and interference channel gains,
largely induced by various space-time processing techniques, it is highly
challenging to quantitatively characterize the performance of dense
multi-antenna networks. In this paper, using tools from stochastic geometry, a
tractable framework is proposed for the analytical evaluation of such networks.
The major result is an innovative representation of the coverage probability,
as an induced $\ell_1$-norm of a Toeplitz matrix. This compact representation
incorporates lots of existing analytical results on single- and multi-antenna
networks as special cases, and its evaluation is almost as simple as the
single-antenna case with Rayleigh fading. To illustrate its effectiveness, we
apply the proposed framework to investigate two kinds of prevalent dense
wireless networks, i.e., physical layer security aware networks and
millimeter-wave networks. In both examples, in addition to tractable analytical
results of relevant performance metrics, insightful design guidelines are also
analytically obtained.
