2 research outputs found
Throughput Maximization for Wireless Communication systems with Backscatter- and Cache-assisted UAV Technology
Unmanned aerial vehicle (UAV) has been widely adopted in wireless systems due
to its flexibility, mobility, and agility. Nevertheless, a limited onboard
battery greatly hinders UAV to prolong the serving time from communication
tasks that need a high power consumption in active RF communications.
Fortunately, caching and backscatter communication (BackCom) are appealing
technology for energy efficient communication systems. This motivates us to
investigate a wireless communication network with backscatter- and
cache-assisted UAV technology. We assume a UAV with a cache memory is deployed
as a flying backscatter device (BD), term the UAV-enabled BD (UB), to relay the
source's signals to the destination. Besides, the UAV can harvest energy from
the source's RF signals and then utilizes it for backscattering information to
the destination. In this context, we aim to maximize the total throughput by
jointly optimizing the dynamic time splitting (DTS) ratio, backscatter
coefficient, and the UB's trajectory with caching capability at the UB
corresponding to linear energy harvesting (LEH) and non-linear energy
harvesting (NLEH) models. These formulations are troublesome to directly solve
since they are mixed-integer non-convex problems. To find solutions, we
decompose the original problem into three subproblems, whereas we first
optimize the DTS ratio for a given backscatter coefficient and UB's trajectory,
followed by the backscatter coefficient optimization for a given DTS ratio and
UB's trajectory, and the UB's trajectory is finally optimized for a given DTS
ratio and backscatter coefficient. Finally, the intensive numerical results
demonstrate that our proposed schemes achieve significant throughput gain in
comparison to the benchmark schemes.Comment: 30 pages, 8 figure
UAV-Enabled Wireless Power Transfer: A Tutorial Overview
Unmanned aerial vehicle (UAV)-enabled wireless power transfer (WPT) has
recently emerged as a promising technique to provide sustainable energy supply
for widely distributed low-power ground devices (GDs) in large-scale wireless
networks. Compared with the energy transmitters (ETs) in conventional WPT
systems which are deployed at fixed locations, UAV-mounted aerial ETs can fly
flexibly in the three-dimensional (3D) space to charge nearby GDs more
efficiently. This paper provides a tutorial overview on UAV-enabled WPT and its
appealing applications, in particular focusing on how to exploit UAVs'
controllable mobility via their 3D trajectory design to maximize the amounts of
energy transferred to all GDs in a wireless network with fairness. First, we
consider the single-UAV-enabled WPT scenario with one UAV wirelessly charging
multiple GDs at known locations. To solve the energy maximization problem in
this case, we present a general trajectory design framework consisting of three
innovative approaches to optimize the UAV trajectory, which are multi-location
hovering, successive-hover-and-fly, and time-quantization-based optimization,
respectively. Next, we consider the multi-UAV-enabled WPT scenario where
multiple UAVs cooperatively charge many GDs in a large area. Building upon the
single-UAV trajectory design, we propose two efficient schemes to jointly
optimize multiple UAVs' trajectories, based on the principles of UAV swarming
and GD clustering, respectively. Furthermore, we consider two important
extensions of UAV-enabled WPT, namely UAV-enabled wireless powered
communication networks (WPCN) and UAV-enabled wireless powered mobile edge
computing (MEC)