  As traditional cellular base stations (BSs) are optimized for 2D ground
service, providing 3D connectivity to uncrewed aerial vehicles (UAVs) requires
re-engineering of the existing infrastructure. In this paper, we propose a new
methodology for designing cellular networks that cater for both ground users
and UAV corridors based on Bayesian optimization. We present a case study in
which we maximize the signal-to-interference-plus-noise ratio (SINR) for both
populations of users by optimizing the electrical antenna tilts and the
transmit power employed at each BS. Our proposed optimized network
significantly boosts the UAV performance, with a 23.4dB gain in mean SINR
compared to an all-downtilt, full-power baseline. At the same time, this
optimal tradeoff nearly preserves the performance on the ground, even attaining
a gain of 1.3dB in mean SINR with respect to said baseline. Thanks to its
ability to optimize black-box stochastic functions, the proposed framework is
amenable to maximize any desired function of the SINR or even the capacity per
area.
