483 research outputs found
Distributed drone base station positioning for emergency cellular networks using reinforcement learning
Due to the unpredictability of natural disasters, whenever a catastrophe happens, it is vital that not only emergency rescue teams are prepared, but also that there is a functional communication network infrastructure. Hence, in order to prevent additional losses of human lives, it is crucial that network operators are able to deploy an emergency infrastructure as fast as possible. In this sense, the deployment of an intelligent, mobile, and adaptable network, through the usage of drones—unmanned aerial vehicles—is being considered as one possible alternative for emergency situations. In this paper, an intelligent solution based on reinforcement learning is proposed in order to find the best position of multiple drone small cells (DSCs) in an emergency scenario. The proposed solution’s main goal is to maximize the amount of users covered by the system, while drones are limited by both backhaul and radio access network constraints. Results show that the proposed Q-learning solution largely outperforms all other approaches with respect to all metrics considered. Hence, intelligent DSCs are considered a good alternative in order to enable the rapid and efficient deployment of an emergency communication network
Survey of Important Issues in UAV Communication Networks
Unmanned Aerial Vehicles (UAVs) have enormous potential in the public and
civil domains. These are particularly useful in applications where human lives
would otherwise be endangered. Multi-UAV systems can collaboratively complete
missions more efficiently and economically as compared to single UAV systems.
However, there are many issues to be resolved before effective use of UAVs can
be made to provide stable and reliable context-specific networks. Much of the
work carried out in the areas of Mobile Ad Hoc Networks (MANETs), and Vehicular
Ad Hoc Networks (VANETs) does not address the unique characteristics of the UAV
networks. UAV networks may vary from slow dynamic to dynamic; have intermittent
links and fluid topology. While it is believed that ad hoc mesh network would
be most suitable for UAV networks yet the architecture of multi-UAV networks
has been an understudied area. Software Defined Networking (SDN) could
facilitate flexible deployment and management of new services and help reduce
cost, increase security and availability in networks. Routing demands of UAV
networks go beyond the needs of MANETS and VANETS. Protocols are required that
would adapt to high mobility, dynamic topology, intermittent links, power
constraints and changing link quality. UAVs may fail and the network may get
partitioned making delay and disruption tolerance an important design
consideration. Limited life of the node and dynamicity of the network leads to
the requirement of seamless handovers where researchers are looking at the work
done in the areas of MANETs and VANETs, but the jury is still out. As energy
supply on UAVs is limited, protocols in various layers should contribute
towards greening of the network. This article surveys the work done towards all
of these outstanding issues, relating to this new class of networks, so as to
spur further research in these areas.Comment: arXiv admin note: substantial text overlap with arXiv:1304.3904 by
other author
3D Aerial Highway: The Key Enabler of the Retail Industry Transformation
The retail industry is already facing an inevitable transformation worldwide,
and with the current pandemic situation, it is even accelerating. Indeed,
consumer habits are shifting from brick-and-mortar stores to online shopping.
The bottleneck in the end-to-end online shopping experience remains the
efficient and quick delivery of goods to consumers. In this context, unmanned
aerial vehicle (UAV) technology is seen as a potential solution to address
cargo delivery issues. Hence, the number of cargo-UAVs is expected to skyrocket
in the next few decades and the airspace to become densely crowded. To
successfully deploy UAVs for mass cargo delivery, seamless and reliable
cellular connectivity for highly mobile UAVs is required. There is an urgent
need for organized and connected routes in the sky. Like highways for cargo
trucks, 3D routes in the airspace should be designed for cargo-UAVs to fulfill
their operations safely and efficiently. We refer to these routes as 3D aerial
highway. In this paper, we thoroughly investigate the feasibility of the aerial
highways paradigm. First, we discuss the motivations and concerns of the aerial
highway paradigm. Then, we present our vision of the 3D aerial highway
framework. Finally, we present related connectivity issues and their potential
solutions.Comment: Accepted for publication in IEEE Communications Magazine: Mobile
Communications and Networks Serie
UAV Assisted Public Safety Communications with LTE-Advanced HetNets and FeICIC
Establishing a reliable communication infrastructure at an emergency site is
a crucial task for mission-critical and real-time public safety communications
(PSC). To this end, use of the unmanned aerial vehicles (UAVs) has recently
received extensive interest for PSC to establish reliable connectivity in a
heterogeneous network (HetNet) environment. These UAVs can be deployed as
unmanned aerial base stations (UABSs) as a part of HetNet infrastructure. In
this article, we explore the role of agile UABSs in LTE-Advanced HetNets by
applying 3GPP Release 11 further-enhanced inter-cell interference coordination
(FeICIC) and cell range expansion (CRE) techniques. Through simulations, we
compare the system-wide 5th percentile spectral efficiency (SE) when UABSs are
deployed in a hexagonal grid and when their locations are optimized using a
genetic algorithm, while also jointly optimizing the CRE and the FeICIC
parameters. Our simulation results show that at optimized UABS locations, the
3GPP Release 11 FeICIC with reduced power subframes can provide considerably
better 5th percentile SE than the 3GPP Release~10 with almost blank subframes.Comment: Accepted Proc. IEEE Annual International Symposium on Personal,
Indoor, and Mobile Radio Communications (PIMRC) 201
Dynamic Base Station Repositioning to Improve Spectral Efficiency of Drone Small Cells
With recent advancements in drone technology, researchers are now considering
the possibility of deploying small cells served by base stations mounted on
flying drones. A major advantage of such drone small cells is that the
operators can quickly provide cellular services in areas of urgent demand
without having to pre-install any infrastructure. Since the base station is
attached to the drone, technically it is feasible for the base station to
dynamic reposition itself in response to the changing locations of users for
reducing the communication distance, decreasing the probability of signal
blocking, and ultimately increasing the spectral efficiency. In this paper, we
first propose distributed algorithms for autonomous control of drone movements,
and then model and analyse the spectral efficiency performance of a drone small
cell to shed new light on the fundamental benefits of dynamic repositioning. We
show that, with dynamic repositioning, the spectral efficiency of drone small
cells can be increased by nearly 100\% for realistic drone speed, height, and
user traffic model and without incurring any major increase in drone energy
consumption.Comment: Accepted at IEEE WoWMoM 2017 - 9 pages, 2 tables, 4 figure
Energy and Information Management of Electric Vehicular Network: A Survey
The connected vehicle paradigm empowers vehicles with the capability to
communicate with neighboring vehicles and infrastructure, shifting the role of
vehicles from a transportation tool to an intelligent service platform.
Meanwhile, the transportation electrification pushes forward the electric
vehicle (EV) commercialization to reduce the greenhouse gas emission by
petroleum combustion. The unstoppable trends of connected vehicle and EVs
transform the traditional vehicular system to an electric vehicular network
(EVN), a clean, mobile, and safe system. However, due to the mobility and
heterogeneity of the EVN, improper management of the network could result in
charging overload and data congestion. Thus, energy and information management
of the EVN should be carefully studied. In this paper, we provide a
comprehensive survey on the deployment and management of EVN considering all
three aspects of energy flow, data communication, and computation. We first
introduce the management framework of EVN. Then, research works on the EV
aggregator (AG) deployment are reviewed to provide energy and information
infrastructure for the EVN. Based on the deployed AGs, we present the research
work review on EV scheduling that includes both charging and vehicle-to-grid
(V2G) scheduling. Moreover, related works on information communication and
computing are surveyed under each scenario. Finally, we discuss open research
issues in the EVN
Edge Computing Enabled by Unmanned Autonomous Vehicles
Pervasive applications are revolutionizing the perception that users have
towards the environment. Indeed, pervasive applications perform resource
intensive computations over large amounts of stream sensor data collected from
multiple sources. This allows applications to provide richer and deep insights
into the natural characteristics that govern everything that surrounds us. A
key limitation of these applications is that they have high energy footprints,
which in turn hampers the quality of experience of users. While cloud and edge
computing solutions can be applied to alleviate the problem, these solutions
are hard to adopt in existing architecture and far from become ubiquitous.
Fortunately, cloudlets are becoming portable enough, such that they can be
transported and integrated into any environment easily and dynamically. In this
article, we investigate how cloudlets can be transported by unmanned autonomous
vehicles (UAV)s to provide computation support on the edge. Based on our study,
we develop GEESE, a novel UAVbased system that enables the dynamic deployment
of an edge computing infrastructure through the cooperation of multiple UAVs
carrying cloudlets. By using GEESE, we conduct rigorous experiments to analyze
the effort to deliver cloudlets using aerial, ground, and underwater UAVs. Our
results indicate that UAVs can work in a cooperative manner to enable edge
computing in the wild
Unmanned Aerial Vehicles: A Survey on Civil Applications and Key Research Challenges
The use of unmanned aerial vehicles (UAVs) is growing rapidly across many
civil application domains including real-time monitoring, providing wireless
coverage, remote sensing, search and rescue, delivery of goods, security and
surveillance, precision agriculture, and civil infrastructure inspection. Smart
UAVs are the next big revolution in UAV technology promising to provide new
opportunities in different applications, especially in civil infrastructure in
terms of reduced risks and lower cost. Civil infrastructure is expected to
dominate the more that $45 Billion market value of UAV usage. In this survey,
we present UAV civil applications and their challenges. We also discuss current
research trends and provide future insights for potential UAV uses.
Furthermore, we present the key challenges for UAV civil applications,
including: charging challenges, collision avoidance and swarming challenges,
and networking and security related challenges. Based on our review of the
recent literature, we discuss open research challenges and draw high-level
insights on how these challenges might be approached.Comment: arXiv admin note: text overlap with arXiv:1602.03602,
arXiv:1704.04813 by other author
Aeronautical Ad Hoc Networking for the Internet-Above-The-Clouds
The engineering vision of relying on the ``smart sky" for supporting air
traffic and the ``Internet above the clouds" for in-flight entertainment has
become imperative for the future aircraft industry. Aeronautical ad hoc
Networking (AANET) constitutes a compelling concept for providing broadband
communications above clouds by extending the coverage of Air-to-Ground (A2G)
networks to oceanic and remote airspace via autonomous and self-configured
wireless networking amongst commercial passenger airplanes. The AANET concept
may be viewed as a new member of the family of Mobile ad hoc Networks (MANETs)
in action above the clouds. However, AANETs have more dynamic topologies,
larger and more variable geographical network size, stricter security
requirements and more hostile transmission conditions. These specific
characteristics lead to more grave challenges in aircraft mobility modeling,
aeronautical channel modeling and interference mitigation as well as in network
scheduling and routing. This paper provides an overview of AANET solutions by
characterizing the associated scenarios, requirements and challenges.
Explicitly, the research addressing the key techniques of AANETs, such as their
mobility models, network scheduling and routing, security and interference are
reviewed. Furthermore, we also identify the remaining challenges associated
with developing AANETs and present their prospective solutions as well as open
issues. The design framework of AANETs and the key technical issues are
investigated along with some recent research results. Furthermore, a range of
performance metrics optimized in designing AANETs and a number of
representative multi-objective optimization algorithms are outlined
Towards UAV Assisted 5G Public Safety Network
Ensuring ubiquitous mission-critical public safety communications (PSC) to all the first responders in the public safety network is crucial at an emergency site. The first responders heavily rely on mission-critical PSC to save lives, property, and national infrastructure during a natural or human-made emergency. The recent advancements in LTE/LTE-Advanced/5G mobile technologies supported by unmanned aerial vehicles (UAV) have great potential to revolutionize PSC.
However, limited spectrum allocation for LTE-based PSC demands improved channel capacity and spectral efficiency. An additional challenge in designing an LTE-based PSC network is achieving at least 95% coverage of the geographical area and human population with broadband rates. The coverage requirement and efficient spectrum use in the PSC network can be realized through the dense deployment of small cells (both terrestrial and aerial). However, there are several challenges with the dense deployment of small cells in an air-ground heterogeneous network (AG-HetNet). The main challenges which are addressed in this research work are integrating UAVs as both aerial user and aerial base-stations, mitigating inter-cell interference, capacity and coverage enhancements, and optimizing deployment locations of aerial base-stations.
First, LTE signals were investigated using NS-3 simulation and software-defined radio experiment to gain knowledge on the quality of service experienced by the user equipment (UE). Using this understanding, a two-tier LTE-Advanced AG-HetNet with macro base-stations and unmanned aerial base-stations (UABS) is designed, while considering time-domain inter-cell interference coordination techniques. We maximize the capacity of this AG-HetNet in case of a damaged PSC infrastructure by jointly optimizing the inter-cell interference parameters and UABS locations using a meta-heuristic genetic algorithm (GA) and the brute-force technique. Finally, considering the latest specifications in 3GPP, a more realistic three-tier LTE-Advanced AG-HetNet is proposed with macro base-stations, pico base-stations, and ground UEs as terrestrial nodes and UABS and aerial UEs as aerial nodes. Using meta-heuristic techniques such as GA and elitist harmony search algorithm based on the GA, the critical network elements such as energy efficiency, inter-cell interference parameters, and UABS locations are all jointly optimized to maximize the capacity and coverage of the AG-HetNet
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