  Herein, an interference-aware predictive aerial-and-terrestrial communication
problem is studied, where an unmanned aerial vehicle (UAV) delivers some data
payload to a few nodes within a communication deadline. The first challenge is
the possible interference to the ground base stations (BSs) and users possibly
at unknown locations. This paper develops a radio-map-based approach to predict
the channel to the receivers and the unintended nodes. Therefore, a predictive
communication strategy can be optimized ahead of time to reduce the
interference power and duration for the ground nodes. Such predictive
optimization raises the second challenge of developing a low-complexity
solution for a batch of transmission strategies over T time slots for N
receivers before the flight. Mathematically, while the proposed
interference-aware predictive communication problem is non-convex, it is
converted into a relaxed convex problem, and solved by a novel dual-based
algorithm, which is shown to achieve global optimality at asymptotically small
slot duration. The proposed algorithm demonstrates orders of magnitude saving
of the computational time for moderate T and N compared to several existing
solvers. Simulations show that the radio-map-assisted scheme can prevent all
unintended receivers with known positions from experiencing interference and
significantly reduce the interference to the users at unknown locations.
