  Flying drones can be used in a wide range of applications and services from
surveillance to package delivery. To ensure robust control and safety of drone
operations, cellular networks need to provide reliable wireless connectivity to
drone user equipments (UEs). To date, existing mobile networks have been
primarily designed and optimized for serving ground UEs, thus making the
mobility support in the sky challenging. In this paper, a novel handover (HO)
mechanism is developed for a cellular-connected drone system to ensure robust
wireless connectivity and mobility support for drone-UEs. By leveraging tools
from reinforcement learning, HO decisions are dynamically optimized using a
Q-learning algorithm to provide an efficient mobility support in the sky. The
results show that the proposed approach can significantly reduce (e.g., by 80%)
the number of HOs, while maintaining connectivity, compared to the baseline HO
scheme in which the drone always connects to the strongest cell.
