32 research outputs found
A Vision and Framework for the High Altitude Platform Station (HAPS) Networks of the Future
A High Altitude Platform Station (HAPS) is a network node that operates in
the stratosphere at an of altitude around 20 km and is instrumental for
providing communication services. Precipitated by technological innovations in
the areas of autonomous avionics, array antennas, solar panel efficiency
levels, and battery energy densities, and fueled by flourishing industry
ecosystems, the HAPS has emerged as an indispensable component of
next-generations of wireless networks. In this article, we provide a vision and
framework for the HAPS networks of the future supported by a comprehensive and
state-of-the-art literature review. We highlight the unrealized potential of
HAPS systems and elaborate on their unique ability to serve metropolitan areas.
The latest advancements and promising technologies in the HAPS energy and
payload systems are discussed. The integration of the emerging Reconfigurable
Smart Surface (RSS) technology in the communications payload of HAPS systems
for providing a cost-effective deployment is proposed. A detailed overview of
the radio resource management in HAPS systems is presented along with
synergistic physical layer techniques, including Faster-Than-Nyquist (FTN)
signaling. Numerous aspects of handoff management in HAPS systems are
described. The notable contributions of Artificial Intelligence (AI) in HAPS,
including machine learning in the design, topology management, handoff, and
resource allocation aspects are emphasized. The extensive overview of the
literature we provide is crucial for substantiating our vision that depicts the
expected deployment opportunities and challenges in the next 10 years
(next-generation networks), as well as in the subsequent 10 years
(next-next-generation networks).Comment: To appear in IEEE Communications Surveys & Tutorial
A Holistic Investigation on Terahertz Propagation and Channel Modeling Toward Vertical Heterogeneous Networks
User-centric and low latency communications can be enabled not only by small
cells but also through ubiquitous connectivity. Recently, the vertical
heterogeneous network (V-HetNet) architecture is proposed to backhaul/fronthaul
a large number of small cells. Like an orchestra, the V-HetNet is a polyphony
of different communication ensembles, including geostationary orbit (GEO), and
low-earth orbit (LEO) satellites (e.g., CubeSats), and networked flying
platforms (NFPs) along with terrestrial communication links. In this study, we
propose the Terahertz (THz) communications to enable the elements of V-HetNets
to function in harmony. As THz links offer a large bandwidth, leading to
ultra-high data rates, it is suitable for backhauling and fronthauling small
cells. Furthermore, THz communications can support numerous applications from
inter-satellite links to in-vivo nanonetworks. However, to savor this harmony,
we need accurate channel models. In this paper, the insights obtained through
our measurement campaigns are highlighted, to reveal the true potential of THz
communications in V-HetNets.Comment: It has been accepted for the publication in IEEE Communications
Magazin
A Prospective Look: Key Enabling Technologies, Applications and Open Research Topics in 6G Networks
The fifth generation (5G) mobile networks are envisaged to enable a plethora
of breakthrough advancements in wireless technologies, providing support of a
diverse set of services over a single platform. While the deployment of 5G
systems is scaling up globally, it is time to look ahead for beyond 5G systems.
This is driven by the emerging societal trends, calling for fully automated
systems and intelligent services supported by extended reality and haptics
communications. To accommodate the stringent requirements of their prospective
applications, which are data-driven and defined by extremely low-latency,
ultra-reliable, fast and seamless wireless connectivity, research initiatives
are currently focusing on a progressive roadmap towards the sixth generation
(6G) networks. In this article, we shed light on some of the major enabling
technologies for 6G, which are expected to revolutionize the fundamental
architectures of cellular networks and provide multiple homogeneous artificial
intelligence-empowered services, including distributed communications, control,
computing, sensing, and energy, from its core to its end nodes. Particularly,
this paper aims to answer several 6G framework related questions: What are the
driving forces for the development of 6G? How will the enabling technologies of
6G differ from those in 5G? What kind of applications and interactions will
they support which would not be supported by 5G? We address these questions by
presenting a profound study of the 6G vision and outlining five of its
disruptive technologies, i.e., terahertz communications, programmable
metasurfaces, drone-based communications, backscatter communications and
tactile internet, as well as their potential applications. Then, by leveraging
the state-of-the-art literature surveyed for each technology, we discuss their
requirements, key challenges, and open research problems
A prospective look: key enabling technologies, applications and open research topics in 6G networks
The fifth generation (5G) mobile networks are envisaged to enable a plethora of breakthrough advancements in wireless technologies, providing support of a diverse set of services over a single platform. While the deployment of 5G systems is scaling up globally, it is time to look ahead for beyond 5G systems. This is mainly driven by the emerging societal trends, calling for fully automated systems and intelligent services supported by extended reality and haptics communications. To accommodate the stringent requirements of their prospective applications, which are data-driven and defined by extremely low-latency, ultra-reliable, fast and seamless wireless connectivity, research initiatives are currently focusing on a progressive roadmap towards the sixth generation (6G) networks, which are expected to bring transformative changes to this premise. In this article, we shed light on some of the major enabling technologies for 6G, which are expected to revolutionize the fundamental architectures of cellular networks and provide multiple homogeneous artificial intelligence-empowered services, including distributed communications, control, computing, sensing, and energy, from its core to its end nodes. In particular, the present paper aims to answer several 6G framework related questions: What are the driving forces for the development of 6G? How will the enabling technologies of 6G differ from those in 5G? What kind of applications and interactions will they support which would not be supported by 5G? We address these questions by presenting a comprehensive study of the 6G vision and outlining seven of its disruptive technologies, i.e., mmWave communications, terahertz communications, optical wireless communications, programmable metasurfaces, drone-based communications, backscatter communications and tactile internet, as well as their potential applications. Then, by leveraging the state-of-the-art literature surveyed for each technology, we discuss the associated requirements, key challenges, and open research problems. These discussions are thereafter used to open up the horizon for future research directions
Drone-assisted emergency communications
Drone-mounted base stations (DBSs) have been proposed to extend coverage and improve communications between mobile users (MUs) and their corresponding macro base stations (MBSs). Different from the base stations on the ground, DBSs can flexibly fly over and close to MUs to establish a better vantage for communications. Thus, the pathloss between a DBS and an MU can be much smaller than that between the MU and MBS. In addition, by hovering in the air, the DBS can likely establish a Line-of-Sight link to the MBS. DBSs can be leveraged to recover communications in a large natural disaster struck area and to fully embody the advantage of drone-assisted communications. In order to retrieve signals from MUs in a large disaster struck area, DBSs need to overcome the large pathloss incurred by the long distance between DBSs and MBSs. This can be addressed by the following two strategies.
First, placing multiple drones in a disaster struck area can be used to mitigate the problem of large backhaul pathloss. In this method, data from MUs in the disaster struck area may be forwarded by more than one drone, i.e., DBSs can enable drone-to-drone communications. Thus, the throughput from the disaster struck area can potentially be enhanced by this multi-drone strategy. A cooperative DBS placement and channel allocation algorithm is proposed to maximize the aggregated data rate from MUs in a disaster struck area. It is demonstrated by simulations that the aggregated data rate can be improved by more than 10%, as compared to the scenario without drone-to-drone communications.
Second, free space optics (FSO) can be used as backhaul links to reduce the backhaul pathloss. FSO can provision a high-speed point-to-point transmission and is thus suitable for backhaul transmission. A heuristic algorithm is proposed to maximize the number of MUs that can be served by the drones by optimizing user association, DBS placement and spectrum allocation iteratively. It is demonstrated by simulations that the proposed algorithm can cover over 15% more MUs at the expense of less than 5% of the aggregated throughput. Equipping DBSs and MBSs with FSO transceivers incurs extra payload for DBSs, hence shortening the hovering time of DBSs. To prolong the hovering time of a DBS, the FSO beam is deployed to facilitate simultaneous communications and charging. The viability of this concept has been studied by varying the distance between a DBS and an MBS, in which an optimal location of the DBS is found to maximize the data throughput, while the charging power directed to the DBS from the MBS diminishes with the increasing distance between them.
Future work is planned to incorporate artificial intelligence to enhance drone-assisted networking for various applications. For example, a drone equipped with a camera can be used to detect victims. By analyzing the captured pictures, the locations of the victims can be estimated by some machine learning based image processing technology