  Terahertz (THz) links require a line-of-sight (LoS) connection, which is hard
to be obtained in most scenarios. For THz communications, analyses based on LoS
probability are not accurate, and a new real LoS model should be considered to
determine the LoS status of the link in a real 3D environment. Considering
unmanned aerial vehicle (UAV)-based THz networks, LoS coverage is analyzed in
this work, where nodes are accurately determined to be in LoS or not.
Specifically, by modeling an environment with 3D blocks, our target is to
locate a set of UAVs equipped with directional THz links to provide LoS
connectivity for the distributed users among the 3D obstacles. To this end, we
first characterize and model the environment with 3D blocks. Then, we propose a
user-friendly algorithm based on 3D spatial vectors, which determines the LoS
status of nodes in the target area. In addition, using 3D modeling, several
meta-heuristic algorithms are proposed for UAVs' positioning under 3D blocks in
order to maximize the LoS coverage percentage. In the second part of the paper,
for a UAV-based THz communication network, a geometrical analysis-based
algorithm is proposed, which jointly clusters the distributed nodes and locates
the set of UAVs to maximize average network capacity while ensuring the LoS
state of distributed nodes among 3D obstacles. Moreover, we also propose a
sub-optimal hybrid k-means-geometrical-based algorithm with a low computational
complexity that can be used for networks where the topology continuously
changes, and thus, users' clustering and UAVs' positioning need to be regularly
updated. Finally, by providing various 3D simulations, we evaluate the effect
of various system parameters such as the number and heights of UAVs, as well as
the density and height of 3D obstacles on the LoS coverage.
