8 research outputs found
Efficiency Maximization for UAV-Enabled Mobile Relaying Systems with Laser Charging
This work studies the joint problem of power and trajectory optimization in
an unmanned aerial vehicle (UAV)-enabled mobile relaying system. In the
considered system, in order to provide convenient and sustainable energy supply
to the UAV relay, we consider the deployment of a power beacon (PB) which can
wirelessly charge the UAV and it is realized by a properly designed laser
charging system. To this end, we propose an efficiency (the weighted sum of the
energy efficiency during information transmission and wireless power
transmission efficiency) maximization problem by optimizing the source/UAV/PB
transmit powers along with the UAV's trajectory. This optimization problem is
also subject to practical mobility constraints, as well as the
information-causality constraint and energy-causality constraint at the UAV.
Different from the commonly used alternating optimization (AO) algorithm, two
joint design algorithms, namely: the concave-convex procedure (CCCP) and
penalty dual decomposition (PDD)-based algorithms, are presented to address the
resulting non-convex problem, which features complex objective function with
multiple-ratio terms and coupling constraints. These two very different
algorithms are both able to achieve a stationary solution of the original
efficiency maximization problem. Simulation results validate the effectiveness
of the proposed algorithms.Comment: 33 pages, 8 figures, accepted for publication in IEEE Transactions on
Wireless Communication
Two-Hop Multi-UAV Relay Network Optimization with Directional Antennas
In this paper, we consider the multi-UAV deployment problem for a two-hop
relaying system. For a better network performance, UAVs carry directional
antennas that are modeled by a realistic radiation pattern. The goal is to
maximize the minimum user rates, and therefore achieve fairness in the network.
We propose an iterative algorithm to optimize the TDMA scheduling in both hops,
UAV trajectories, antenna beamwidths, and transmit power of the base station
and relays. Simulation results show the throughput improvement as a result of
optimizing the directional antenna radiation patterns. In addition, we derive
the optimal power allocation, which combined with the beamwidth optimization
yields to a much better performance.Comment: 30 page
Handling Spontaneous Traffic Variations in 5G+ via Offloading onto mmWave-Capable UAV `Bridges'
Unmanned aerial vehicles (UAVs) are increasingly employed for numerous public
and civil applications, such as goods delivery, medicine, surveillance, and
telecommunications. For the latter, UAVs with onboard communication equipment
may help temporarily offload traffic onto the neighboring cells in
fifth-generation networks and beyond (5G+). In this paper, we propose and
evaluate the use of UAVs traveling over the area of interest to relieve
congestion in 5G+ systems under spontaneous traffic fluctuations. To this end,
we assess two inherently different offloading schemes, named routed and
controlled UAV `bridging'. Using the tools of renewal theory and stochastic
geometry, we analytically characterize these schemes in terms of the fraction
of traffic demand that can be offloaded onto the UAV `bridge' as our parameter
of interest. This framework accounts for the unique features of millimeter-wave
(mmWave) radio propagation and city deployment types with potential
line-of-sight (LoS) link blockage by buildings. We also introduce enhancements
to the proposed schemes that significantly improve the offloading gains. Our
findings offer evidence that the UAV `bridges' may be used for efficient
traffic offloading in various urban scenarios.Comment: This work has been accepted for publication in the IEEE Transactions
on Vehicular Technolog