  In this paper, we study to employ geographic information to address the
blockage problem of air-to-ground links between UAV and terrestrial nodes. In
particular, a UAV relay is deployed to establish communication links from a
ground base station to multiple ground users. To improve communication
capacity, we first model the blockage effect caused by buildings according to
the three-dimensional (3-D) geographic information. Then, an optimization
problem is formulated to maximize the minimum capacity among users by jointly
optimizing the 3-D position and power allocation of the UAV relay, under the
constraints of link capacity, maximum transmit power, and blockage. To solve
this complex non-convex problem, a two-loop optimization framework is developed
based on Lagrangian relaxation. The outer-loop aims to obtain proper Lagrangian
multipliers to ensure the solution of the Lagrangian problem converge to the
tightest upper bound on the original problem. The inner-loop solves the
Lagrangian problem by applying the block coordinate descent (BCD) and
successive convex approximation (SCA) techniques, where UAV 3-D positioning and
power allocation are alternately optimized in each iteration. Simulation
results confirm that the proposed solution significantly outperforms two
benchmark schemes and achieves a performance close to the upper bound on the
UAV relay system.

Signal Processing