  As an alternative solution for quick disaster recovery of backhaul/fronthaul
links, in this paper, a dynamic unmanned aerial vehicles (UAV)-assisted
heterogeneous (HetNet) network equipped with directional terahertz (THz)
antennas is studied to solve the problem of transferring traffic of distributed
small cells. To this end, we first characterize a detailed three-dimensional
modeling of the dynamic UAV-assisted HetNet, and then, we formulate the problem
for UAV trajectory to minimize the maximum outage probability of directional
THz links. Then, using deep reinforcement learning (DRL) method, we propose an
efficient algorithm to learn the optimal trajectory. Finally, using
simulations, we investigate the performance of the proposed DRL-based
trajectory method.
