Reference : 5G AND BEYOND NETWORKS WITH UAV: TRAJECTORY DESIGN AND RESOURCE ALLOCATION
Dissertations and theses : Doctoral thesis
Engineering, computing & technology : Computer science
Security, Reliability and Trust
http://hdl.handle.net/10993/49300
5G AND BEYOND NETWORKS WITH UAV: TRAJECTORY DESIGN AND RESOURCE ALLOCATION
English
Tran Dinh, Hieu mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom >]
24-Nov-2021
University of Luxembourg, ​​Luxembourg
DOCTOR OF THE UNIVERSITY OF LUXEMBOURG IN COMPUTER SCIENCE
207
Ottersten, Björn mailto
Chatzinotas, Symeon mailto
A. Olivares-Mendez, Miguel mailto
Ejder, Baştuğ mailto
Ngo, Quoc Hien mailto
[en] unmanned aerial vehicles (UAVs) ; 5G ; UAV communications ; Emergency communications ; Trajectory design
[en] Over the past few years, unmanned aerial vehicle (UAV)-enabled wireless communications
have attracted considerable attention from both academia and industry due to their
high mobility, low cost, strong light-of-sight communication links, and ease of deployment.
Specifically, UAVs can be deployed to serve as aerial base stations (BSs), relays, power
sources, etc., to support ground users (GUs) in various scenarios such as surveillance missions,
search and rescue, crop monitoring, delivery of goods, data collection, emergency
communications, secrecy communications, space-air-ground communications, etc. Despite
many advantages, UAV-enabled communications are not without limitations. The limitations
of UAVs have imposed technical restrictions on weight, size, and energy capability,
thereby affecting the durability and performance of UAVs. The key goal of this dissertation
is to propose and develop new frameworks and efficient optimization algorithms to solve
novel challenging problems, facilitate the design and deployment of UAV-enabled communications.
Consequently, these proposed algorithms can become one of the foundations
for deploying UAVs in future wireless systems. Specifically, this dissertation investigates
different UAV communication systems by addressing several important research problems
through four emerging scenarios: 1) Design UAV trajectory based on traveling salesman
problem with time window (TSPTW); 2) Full-duplex (FD) UAV relay-assisted emergency
communications in Internet of Things (IoT) networks; 3) Backscatter- and cache-assisted
UAV communications; and 4) Satellite- and cache-assisted UAV communications in 6G
aerial networks.
In the first scenario, we provide the coarse trajectory for the UAV based on TSPTW,
which has not been investigated in UAV communications yet. Concretely, we propose two
trajectory design algorithms based on TSPTW, namely heuristic algorithm and dynamic
programming (DP)-based algorithm, and they are compared with exhaustive search and
traveling salesman problem (TSP)-based methods. Based on the feasible path obtained
from proposed algorithms, we minimize the total UAV’s energy consumption for each given
path via a joint optimization of the UAV velocities in all hops. Simulation results show that the energy consumption value of DP is very close to that of the exhaustive algorithm
with greatly reduced complexity. Based on this work, an efficient TSPTW-based algorithm
can be used as an initialized trajectory for designing a joint problem of UAV trajectory and
other communications factors (e.g., communication scheduling, transmit power allocation,
time allocation), which are challenges.
We then study the case of a FD UAV relaying system in IoT networks. Specifically, a
UAV can be deployed as a flying base station (BS) to collect data from time-constrained
IoT devices and then transfer it to a ground gateway (GW). Especially, the impact of
latency constraint for the uplink (UL) and downlink (DL) transmission utilizing FD or
half-duplex (HD) mode is investigated. Using the proposed system model, we aim to
maximize the total number of served IoT devices subject to the maximum speed constraint
of the UAV, total traveling time constant, UAV trajectory, maximum transmit power at
the devices/UAV, limited cache size of the UAV, and latency constraints for both UL and
DL. Next, we attempt to maximize the total throughput subject to the number of served
IoT devices. The outcome of this work will motivate a new framework for UAV-aided
communications in disaster or emergency communications.
Next, a novel system model that considers SWIPT, backscatter and caching in UAV
wireless networks is developed. Based on this model, we aim to maximize the system
throughput by jointly optimizing the dynamic time splitting (DTS) ratio and the UAV’s
trajectory with caching capability at the UAV. This is the first work that jointly considers
wireless power transfer (WPT), caching, and BackCom in UAV communications, which
provides a potential solution for a battery-free drone system that can fly for a long period
in the sky to support the terrestrial communication systems.
Finally, a novel system model for effective use of LEO satellite- and cache-assisted UAV
communication is proposed and studied. Specifically, caching is provided by the UAV to
reduce backhaul congestion, and the LEO satellite assists the UAV’s backhaul link. In this
context, we aim to maximize the minimum achievable throughput per ground user (GU)
by jointly optimizing cache placement, the UAV’s transmit power, bandwidth allocation,
and trajectory with a limited cache capacity and operation time. The outcomes of this
work can provide a new design framework for Satellite-UAV-terrestrial communications
that includes two tiers, i.e., the backhaul link from satellite to UAV and the access link
from UAV to ground users, which imposes new challenges and was not investigated before.
Interdisciplinary Centre for Security, Reliability and Trust-SigCom
FNR CORE ProCAST, (Budget code: R-STR-5010-00-Z), grant C17/IS/11691338 ; FNR 5G-Sky, grant C19/IS/13713801
FNR CORE ProCAST
Researchers ; Professionals ; Students ; General public ; Others
http://hdl.handle.net/10993/49300
FnR ; FNR11691338 > Bjorn Ottersten > ProCAST > Proactive Edge Caching For Content Delivery Networks Powered By Hybrid Satellite/Terrestrial Backhauling > 01/07/2018 > 30/06/2021 > 2017

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