  Mobile base stations on board unmanned aerial vehicles (UAVs) promise to
deliver connectivity to those areas where the terrestrial infrastructure is
overloaded, damaged, or absent. A fundamental problem in this context involves
determining a minimal set of locations in 3D space where such aerial base
stations (ABSs) must be deployed to provide coverage to a set of users. While
nearly all existing approaches rely on average characterizations of the
propagation medium, this work develops a scheme where the actual channel
information is exploited by means of a radio tomographic map. A convex
optimization approach is presented to minimize the number of required ABSs
while ensuring that the UAVs do not enter no-fly regions. A simulation study
reveals that the proposed algorithm markedly outperforms its competitors.
