  Today's growth in the volume of wireless devices coupled with the promise of
supporting data-intensive 5G-&-beyond use cases is driving the industry to
deploy more millimeter-wave (mmWave) base stations (BSs). Although mmWave
cellular systems can carry a larger volume of traffic, dense deployment, in
turn, increases the BS installation and maintenance cost, which has been
largely ignored in their utilization. In this paper, we present an approach to
the problem of mmWave BS deployment in urban environments by minimizing BS
deployment cost subject to BS association and user equipment (UE) outage
constraints. By exploiting the macro diversity, which enables each UE to be
associated with multiple BSs, we derive an expression for UE outage that
integrates physical blockage, UE access-limited blockage, and
signal-to-interference-plus-noise-ratio (SINR) outage into its expression. The
minimum-cost BS deployment problem is then formulated as integer non-linear
programming (INP). The combinatorial nature of the problem motivates the
pursuit of the optimal solution by decomposing the original problem into the
two separable subproblems, i.e., cell coverage optimization and minimum subset
selection subproblems. We provide the optimal solution and theoretical
justifications for each subproblem. The simulation results demonstrating UE
outage guarantees of the proposed method are presented. Interestingly, the
proposed method produces a unique distribution of the macro-diversity orders
over the network that is distinct from other benchmarks.
