  In this paper, we propose a novel energy-efficient data collection and
wireless power transfer (WPT) framework for internet of things (IoT)
applications, via a multiple-input multiple-output (MIMO) full-duplex (FD)
unmanned aerial vehicle (UAV). To exploit the benefits of UAV-enabled WPT and
MIMO FD communications, we allow the MIMO FD UAV charge low-power IoT devices
while at the same time collect data from them. With the aim of saving the total
energy consumed at the UAV, we formulate an energy minimization problem by
taking the FD hardware impairments, the number of uploaded data bits, and the
energy harvesting causality into account. Due to the non-convexity of the
problem in terms of UAV trajectory and transmit beamforming for WPT, tracking
the global optimality is quite challenge. Alternatively, we find a local
optimal point by implementing the proposed iterative search algorithm combining
with successive convex approximation techniques. Numerical results show that
the proposed approach can lead to superior performance compared with other
benchmark schemes with low computational complexity and fast convergence.
