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.