  Leveraging unmanned aerial vehicle (UAV) is convenient to collect data from
ground sensor. However, in the presence of unknown urban environment, the data
collection is subject to the blockage of urban buildings. In this paper,
considering the urban environment during flight, we propose dynamic adaptive
modulation and height control for UAV-sensor data harvesting in urban areas. In
each time slot, the modulation format and flight height are selected based on
current system states, with the aim of minimizing the expected transmission
energy of sensor under data volume and flight height constraints. The dynamic
adaptive modulation and height control problem is formulated as constrained
finite-horizon Markov decision processes (CMDP), which can be solved by
backward induction algorithm. The advantage of proposed joint design over
modulation selection only is illustrated via the computer simulations, where
48.23% expected transmission energy can be saved for ground sensor.
