  In this paper, we consider a UAV-enabled WSN where a flying UAV is employed
to collect data from multiple sensor nodes (SNs). Our objective is to maximize
the minimum average data collection rate from all SNs subject to a prescribed
reliability constraint for each SN by jointly optimizing the UAV communication
scheduling and three-dimensional (3D) trajectory. Different from the existing
works that assume the simplified line-of-sight (LoS) UAV-ground channels, we
consider the more practically accurate angle-dependent Rician fading channels
between the UAV and SNs with the Rician factors determined by the corresponding
UAV-SN elevation angles. However, the formulated optimization problem is
intractable due to the lack of a closed-form expression for a key parameter
termed effective fading power that characterizes the achievable rate given the
reliability requirement in terms of outage probability. To tackle this
difficulty, we first approximate the parameter by a logistic ('S' shape)
function with respect to the 3D UAV trajectory by using the data regression
method. Then the original problem is reformulated to an approximate form,
which, however, is still challenging to solve due to its non-convexity. As
such, we further propose an efficient algorithm to derive its suboptimal
solution by using the block coordinate descent technique, which iteratively
optimizes the communication scheduling, the UAV's horizontal trajectory, and
its vertical trajectory. The latter two subproblems are shown to be non-convex,
while locally optimal solutions are obtained for them by using the successive
convex approximation technique. Last, extensive numerical results are provided
to evaluate the performance of the proposed algorithm and draw new insights on
the 3D UAV trajectory under the Rician fading as compared to conventional LoS
channel models.
