318 research outputs found
Hybrid Satellite-Terrestrial Communication Networks for the Maritime Internet of Things: Key Technologies, Opportunities, and Challenges
With the rapid development of marine activities, there has been an increasing
number of maritime mobile terminals, as well as a growing demand for high-speed
and ultra-reliable maritime communications to keep them connected.
Traditionally, the maritime Internet of Things (IoT) is enabled by maritime
satellites. However, satellites are seriously restricted by their high latency
and relatively low data rate. As an alternative, shore & island-based base
stations (BSs) can be built to extend the coverage of terrestrial networks
using fourth-generation (4G), fifth-generation (5G), and beyond 5G services.
Unmanned aerial vehicles can also be exploited to serve as aerial maritime BSs.
Despite of all these approaches, there are still open issues for an efficient
maritime communication network (MCN). For example, due to the complicated
electromagnetic propagation environment, the limited geometrically available BS
sites, and rigorous service demands from mission-critical applications,
conventional communication and networking theories and methods should be
tailored for maritime scenarios. Towards this end, we provide a survey on the
demand for maritime communications, the state-of-the-art MCNs, and key
technologies for enhancing transmission efficiency, extending network coverage,
and provisioning maritime-specific services. Future challenges in developing an
environment-aware, service-driven, and integrated satellite-air-ground MCN to
be smart enough to utilize external auxiliary information, e.g., sea state and
atmosphere conditions, are also discussed
A Survey on Cellular-connected UAVs: Design Challenges, Enabling 5G/B5G Innovations, and Experimental Advancements
As an emerging field of aerial robotics, Unmanned Aerial Vehicles (UAVs) have
gained significant research interest within the wireless networking research
community. As soon as national legislations allow UAVs to fly autonomously, we
will see swarms of UAV populating the sky of our smart cities to accomplish
different missions: parcel delivery, infrastructure monitoring, event filming,
surveillance, tracking, etc. The UAV ecosystem can benefit from existing 5G/B5G
cellular networks, which can be exploited in different ways to enhance UAV
communications. Because of the inherent characteristics of UAV pertaining to
flexible mobility in 3D space, autonomous operation and intelligent placement,
these smart devices cater to wide range of wireless applications and use cases.
This work aims at presenting an in-depth exploration of integration synergies
between 5G/B5G cellular systems and UAV technology, where the UAV is integrated
as a new aerial User Equipment (UE) to existing cellular networks. In this
integration, the UAVs perform the role of flying users within cellular
coverage, thus they are termed as cellular-connected UAVs (a.k.a. UAV-UE,
drone-UE, 5G-connected drone, or aerial user). The main focus of this work is
to present an extensive study of integration challenges along with key 5G/B5G
technological innovations and ongoing efforts in design prototyping and field
trials corroborating cellular-connected UAVs. This study highlights recent
progress updates with respect to 3GPP standardization and emphasizes
socio-economic concerns that must be accounted before successful adoption of
this promising technology. Various open problems paving the path to future
research opportunities are also discussed.Comment: 30 pages, 18 figures, 9 tables, 102 references, journal submissio
Reliable and Secure Drone-assisted MillimeterWave Communications
The next generation of mobile networks and wireless communication, including the fifth-generation (5G) and beyond, will provide a high data rate as one of its fundamental requirements. Providing high data rates can be accomplished through communication over high-frequency bands such as the Millimeter-Wave(mmWave) one. However, mmWave communication experiences short-range communication, which impacts the overall network connectivity. Improving network connectivity can be accomplished through deploying Unmanned Ariel Vehicles(UAVs), commonly known as drones, which serve as aerial small-cell base stations. Moreover, drone deployment is of special interest in recovering network connectivity in the aftermath of disasters. Despite the potential advantages, drone-assisted networks can be more vulnerable to security attacks, given their limited capabilities. This security vulnerability is especially true in the aftermath of a disaster where security measures could be at their lowest. This thesis focuses on drone-assisted mmWave communication networks with their potential to provide reliable communication in terms of higher network connectivity measures, higher total network data rate, and lower end-to-end delay. Equally important, this thesis focuses on proposing and developing security measures needed for drone-assisted networks’ secure operation. More specifically, we aim to employ a swarm of drones to have more connection, reliability, and secure communication over the mmWave band. Finally, we target both the cellular 5Gnetwork and Ad hoc IEEE802.11ad/ay in typical network deployments as well as in post-disaster circumstances
Architecture design for disaster resilient management network using D2D technology
Huge damages from natural disasters, such as earthquakes, floods, landslide, tsunamis, have been reported in recent years, claiming many lives, rendering millions homeless and causing huge financial losses worldwide. The lack of effective communication between the public rescue/safety agencies, rescue teams, first responders and trapped survivors/victims makes the situation even worse. Factors like dysfunctional communication networks, limited communications capacity, limited resources/services, data transformation and effective evaluation, energy, and power deficiency cause unnecessary hindrance in rescue and recovery services during a disaster. The new wireless communication technologies are needed to enhance life-saving capabilities and rescue services. In general, in order to improve societal resilience towards natural catastrophes and develop effective communication infrastructure, innovative approaches need to be initiated to provide improved quality, better connectivity in the events of natural and human disasters.
In this thesis, a disaster resilient network architecture is proposed and analysed using multi-hop communications, clustering, energy harvesting, throughput optimization, reliability enhancement, adaptive selection, and low latency communications. It also examines the importance of mode selection, power management, frequency and time resource allocation to realize the promises of Long-term Evolution (LTE) Device to Device (D2D) communication. In particular, to support resilient and energy efficient communication in disaster-affected areas.
This research is examined by thorough and vigorous simulations and validated through mathematical modelling. Overall, the impact of this research is twofold: i) it provides new technologies for effective inter- and intra-agency coordination system during a disaster event by establishing a stronger and resilient communication; and ii) It offers a potential solution for stakeholders such as governments, rescue teams, and general public with new informed information on how to establish effective policies to cope with challenges before, during and after the disaster events
6G White Paper on Machine Learning in Wireless Communication Networks
The focus of this white paper is on machine learning (ML) in wireless
communications. 6G wireless communication networks will be the backbone of the
digital transformation of societies by providing ubiquitous, reliable, and
near-instant wireless connectivity for humans and machines. Recent advances in
ML research has led enable a wide range of novel technologies such as
self-driving vehicles and voice assistants. Such innovation is possible as a
result of the availability of advanced ML models, large datasets, and high
computational power. On the other hand, the ever-increasing demand for
connectivity will require a lot of innovation in 6G wireless networks, and ML
tools will play a major role in solving problems in the wireless domain. In
this paper, we provide an overview of the vision of how ML will impact the
wireless communication systems. We first give an overview of the ML methods
that have the highest potential to be used in wireless networks. Then, we
discuss the problems that can be solved by using ML in various layers of the
network such as the physical layer, medium access layer, and application layer.
Zero-touch optimization of wireless networks using ML is another interesting
aspect that is discussed in this paper. Finally, at the end of each section,
important research questions that the section aims to answer are presented
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