  Optimal deployment and movement of multiple unmanned aerial vehicles (UAVs)
is studied. The considered scenario consists of several ground terminals (GTs)
communicating with the UAVs using variable transmission power and fixed data
rate. First, the static case of a fixed geographical GT density is analyzed.
Using high resolution quantization theory, the corresponding best achievable
performance (measured in terms of the average GT transmission power) is
determined in the asymptotic regime of a large number of UAVs. Next, the
dynamic case where the GT density is allowed to vary periodically through time
is considered. For one-dimensional networks, an accurate formula for the total
UAV movement that guarantees the best time-averaged performance is determined.
In general, the tradeoff between the total UAV movement and the achievable
performance is obtained through a Lagrangian approach. A corresponding
trajectory optimization algorithm is introduced and shown to guarantee a
convergent Lagrangian. Numerical simulations confirm the analytical findings.
Extensions to different system models and performance measures are also
discussed.
