  Due to their passive nature and thus low energy consumption, intelligent
reflecting surfaces (IRSs) have shown promise as means of extending coverage as
a proxy for connection reliability. The relative locations of the base station
(BS), IRS, and user equipment (UE) determine the extent of the coverage that
the IRS provides which demonstrates the importance of the IRS placement
problem. More specifically, locations, which determine whether BS-IRS and
IRS-UE line of sight (LOS) links exist, and surface orientation, which
determines whether the BS and UE are within the field of view (FoV) of the
surface, play crucial roles in the quality of provided coverage. Moreover,
another challenge is high computational complexity, since the IRS placement
problem is a combinatorial optimization, and is NP-hard. Identifying the
orientation of the surface and LOS channel as two crucial factors, we propose
an efficient IRS placement algorithm that takes these two characteristics into
account in order to maximize the network coverage. We prove the submodularity
of the objective function which establishes near-optimal performance bounds for
the algorithm. Simulation results demonstrate the performance of the proposed
algorithm in a real environment.
