  Despite the trend towards ubiquitous wireless connectivity, there are
scenarios where the communications infrastructure is damaged and wireless
coverage is insufficient or does not exist, such as in natural disasters and
temporary crowded events. Flying networks, composed of Unmanned Aerial Vehicles
(UAV), have emerged as a flexible and cost-effective solution to provide
on-demand wireless connectivity in these scenarios. UAVs have the capability to
operate virtually everywhere, and the growing payload capacity makes them
suitable platforms to carry wireless communications hardware. The state of the
art in the field of flying networks is mainly focused on the optimal
positioning of the flying nodes, while the wireless link parameters are
configured with default values. On the other hand, current link adaptation
algorithms are mainly targeting fixed or low mobility scenarios.
  We propose a novel rate adaptation approach for flying networks, named
Trajectory Aware Rate Adaptation (TARA), which leverages the knowledge of
flying nodes' movement to predict future channel conditions and perform rate
adaptation accordingly. Simulation results of 100 different trajectories show
that our solution increases throughput by up to 53% and achieves an average
improvement of 14%, when compared with conventional rate adaptation algorithms
such as Minstrel-HT.
