6 research outputs found
Joint Communication and Motion Energy Minimization in UGV Backscatter Communication
While backscatter communication emerges as a promising solution to reduce
power consumption at IoT devices, the transmission range of backscatter
communication is short. To this end, this work integrates unmanned ground
vehicles (UGVs) into the backscatter system. With such a scheme, the UGV could
facilitate the communication by approaching various IoT devices. However,
moving also costs energy consumption and a fundamental question is: what is the
right balance between spending energy on moving versus on communication? To
answer this question, this paper proposes a joint graph mobility and
backscatter communication model. With the proposed model, the total energy
minimization at UGV is formulated as a mixed integer nonlinear programming
(MINLP) problem. Furthermore, an efficient algorithm that achieves a local
optimal solution is derived, and it leads to automatic trade-off between
spending energy on moving versus on communication. Numerical results are
provided to validate the performance of the proposed algorithm.Comment: Proc. IEEE ICC'19, Shanghai, China, May 2019, 6 page
Charging Wireless Sensor Networks with Mobile Charger and Infrastructure Pivot Cluster Heads
Wireless rechargeable sensor networks (WRSNs) consisting of sensor nodes with
batteries have been at the forefront of sensing and communication technologies
in the last few years. Sensor networks with different missions are being
massively rolled out, particularly in the internet-of-things commercial market.
To ensure sustainable operation of WRSNs, charging in a timely fashion is very
important, since lack of energy of even a single sensor node could result in
serious outcomes. With the large number of WRSNs existing and to be existed,
energy-efficient charging schemes are becoming indispensable to workplaces that
demand a proper level of operating cost. Selection of charging scheme depends
on network parameters such as the distribution pattern of sensor nodes, the
mobility of the charger, and the availability of the directional antenna. Among
current charging techniques, radio frequency (RF) remote charging with a small
transmit antenna is gaining interest when non-contact type charging is required
for sensor nodes. RF charging is particularly useful when sensor nodes are
distributed in the service area. To obtain higher charging efficiency with RF
charging, optimal path planning for mobile chargers, and the beamforming
technique, implemented by making use of a directional antenna, can be
considered. In this article, we present a review of RF charging for WRSNs from
the perspectives of charging by mobile charger, harvesting using sensor nodes,
and energy trading between sensor nodes. The concept of a pivot cluster head is
introduced and a novel RF charging scheme in two stages, consisting of charging
pivot cluster heads by a mobile charger with a directional antenna and charging
member sensor nodes by pivot cluster heads with directional antennae, is
presented.Comment: to be submitted to an SCI journa
UAV-Enabled Wireless Power Transfer: Trajectory Design and Energy Region Characterization
This paper studies a new unmanned aerial vehicle (UAV)-enabled wireless power
transfer (WPT) system, where a UAV-mounted energy transmitter (ET) broadcasts
wireless energy to charge distributed energy receivers (ERs) on the ground. In
particular, we consider a basic two-user scenario, and investigate how the UAV
can optimally exploit its mobility to maximize the amount of energy transferred
to the two ERs during a given charging period. We characterize the achievable
energy region of the two ERs, by optimizing the UAV's trajectory subject to a
maximum speed constraint. We show that when the distance between the two ERs is
smaller than a certain threshold, the boundary of the energy region is achieved
when the UAV hovers above a fixed location between them for all time; while
when their distance is larger than the threshold, to achieve the boundary of
the energy region, the UAV in general needs to hover and fly between two
different locations above the line connecting them. Numerical results show that
the optimized UAV trajectory can significantly improve the WPT efficiency and
fairness of the two ERs, especially when the UAV's maximum speed is large
and/or the charging duration is long.Comment: Submitted for possible conference publicatio
Throughput Maximization for UAV-Enabled Wireless Powered Communication Networks
This paper studies an unmanned aerial vehicle (UAV)-enabled wireless powered
communication network (WPCN), in which a UAV is dispatched as a mobile access
point (AP) to serve a set of ground users periodically. The UAV employs the
radio frequency (RF) wireless power transfer (WPT) to charge the users in the
downlink, and the users use the harvested RF energy to send independent
information to the UAV in the uplink. Unlike the conventional WPCN with fixed
APs, the UAV-enabled WPCN can exploit the mobility of the UAV via trajectory
design, jointly with the wireless resource allocation optimization, to maximize
the system throughput. In particular, we aim to maximize the uplink common
(minimum) throughput among all ground users over a finite UAV's flight period,
subject to its maximum speed constraint and the users' energy neutrality
constraints. The resulted problem is non-convex and thus difficult to be solved
optimally. To tackle this challenge, we first consider an ideal case without
the UAV's maximum speed constraint, and obtain the optimal solution to the
relaxed problem. The optimal solution shows that the UAV should successively
hover above a finite number of ground locations for downlink WPT, as well as
above each of the ground users for uplink communication. Next, we consider the
general problem with the UAV's maximum speed constraint. Based on the above
multi-location-hovering solution, we first propose an efficient successive
hover-and-fly trajectory design, jointly with the downlink and uplink wireless
resource allocation, and then propose a locally optimal solution by applying
the techniques of alternating optimization and successive convex programming
(SCP). Numerical results show that the proposed UAV-enabled WPCN achieves
significant throughput gains over the conventional WPCN with fixed-location AP.Comment: To appear in the IEEE IoT Journa
UAV-Enabled Wireless Power Transfer: Trajectory Design and Energy Optimization
This paper studies a new unmanned aerial vehicle (UAV)-enabled wireless power
transfer (WPT) system, where a UAV-mounted mobile energy transmitter (ET) is
dispatched to deliver wireless energy to a set of on-ground energy receivers
(ERs). We investigate how the UAV should optimally exploit its mobility via
trajectory design to maximize the energy transferred to all ERs during a finite
period. First, we consider the maximization of the sum energy received by all
ERs by optimizing the UAV's trajectory subject to its maximum speed constraint.
We obtain its optimal solution, which shows that the UAV should hover at one
single fixed location during the whole period. However, the sum-energy
maximization incurs a "near-far" fairness issue. To overcome this issue, we
consider a different problem to maximize the minimum received energy among all
ERs. We first consider an ideal case by ignoring the UAV's maximum speed
constraint, and show that the relaxed problem can be optimally solved via the
Lagrange dual method. Then, for the general case with the UAV's maximum speed
constraint considered, we propose a new successive hover-and-fly trajectory
motivated by the optimal trajectory in the ideal case, and obtain efficient
trajectory designs by applying the successive convex programing (SCP).Comment: Submitted for possible journal publicatio
Backscatter Data Collection with Unmanned Ground Vehicle: Mobility Management and Power Allocation
Collecting data from massive Internet of Things (IoT) devices is a
challenging task, since communication circuits are power-demanding while energy
supply at IoT devices is limited. To overcome this challenge, backscatter
communication emerges as a promising solution as it eliminates radio frequency
components in IoT devices. Unfortunately, the transmission range of backscatter
communication is short. To facilitate backscatter communication, this work
proposes to integrate unmanned ground vehicle (UGV) with backscatter data
collection. With such a scheme, the UGV could improve the communication quality
by approaching various IoT devices. However, moving also costs energy
consumption and a fundamental question is: what is the right balance between
spending energy on moving versus on communication? To answer this question,
this paper studies energy minimization under a joint graph mobility and
backscatter communication model. With the joint model, the mobility management
and power allocation problem unfortunately involves nonlinear coupling between
discrete variables brought by mobility and continuous variables brought by
communication. Despite the optimization challenges, an algorithm that
theoretically achieves the minimum energy consumption is derived, and it leads
to automatic trade-off between spending energy on moving versus on
communication in the UGV backscatter system. Simulation results show that if
the noise power is small (e.g., -100 dBm), the UGV should collect the data with
small movements. However, if the noise power is increased to a larger value
(e.g., -60 dBm), the UGV should spend more motion energy to get closer to IoT
users.Comment: Journal paper with 15 page