186 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 cognitive control approach to interference mitigation in communications-based train control (CBTC) co-existing with passenger information systems (PISs)
As a key component of urban rail transit systems, communications-based train control (CBTC) is an automated train control system using train-ground communications to ensure efficient operation of rail vehicles. In addition to CBTC systems, passenger information systems (PISs) are adopted in urban rail transit systems to improve quality of service (QoS) offered to customers. The interference between CBTC systems and PISs is an important factor impacting QoS of both CBTC systems and PISs. With recent advances in cognitive dynamic systems, in this paper, we take a cognitive control approach to interference mitigation considering the co-existence of CBTC systems and PISs. In our cognitive control approach, the notion of information gap is adopted to quantitatively describe effects of interference on CBTC. The wireless channel is modeled as a finite-state Markov chain with multiple state transition probability matrices, which are derived from real field measurements. Simulation results show that the proposed cognitive control approach can significantly improve performance of CBTC train-ground communications under interference from
DETECTION AND ALLEVIATION OF LAST-MILE WIRELESS LINK BOTTLENECKS
Ph.DDOCTOR OF PHILOSOPH
Efficient radio resource management in next generation wireless networks
The current decade has witnessed a phenomenal growth in mobile wireless communication
networks and subscribers. In 2015, mobile wireless devices and connections were reported to have grown to about 7.9 billion, exceeding human
population. The explosive growth in mobile wireless communication network subscribers has created a huge demand for wireless network capacity,
ubiquitous wireless network coverage, and enhanced Quality of Service (QoS). These demands have led to several challenging problems for wireless
communication networks operators and designers. The Next Generation Wireless Networks (NGWNs) will support high mobility communications, such as
communication in high-speed rails. Mobile users in such high mobility environment demand reliable QoS, however, such users are plagued with a
poor signal-tonoise ratio, due to the high vehicular penetration loss, increased transmission outage and handover information overhead, leading
to poor QoS provisioning for the networks' mobile users. Providing a reliable QoS for high mobility users remains one of the unique challenges
for NGWNs. The increased wireless network capacity and coverage of NGWNs means that mobile communication users at the cell-edge should have
enhanced network performance. However, due to path loss (path attenuation), interference, and radio background noise, mobile communication
users at the cell-edge can experience relatively poor transmission channel qualities and subsequently forced to transmit at a low bit transmission
rate, even when the wireless communication networks can support high bit transmission rate. Furthermore, the NGWNs are envisioned to be Heterogeneous
Wireless Networks (HWNs). The NGWNs are going to be the integration platform of diverse homogeneous wireless communication networks for a convergent
wireless communication network. The HWNs support single and multiple calls (group calls), simultaneously. Decision making is an integral core of radio
resource management. One crucial decision making in HWNs is network selection. Network selection addresses the problem of how to select the best
available access network for a given network user connection. For the integrated platform of HWNs to be truly seamless and
efficient, a robust and stable wireless access network selection algorithm is needed. To meet these challenges for the
different mobile wireless communication network users, the NGWNs will have to provide a great leap in wireless network capacity, coverage,
QoS, and radio resource utilization. Moving wireless communication networks (mobile hotspots) have been proposed as a solution to providing
reliable QoS to high mobility users. In this thesis, an Adaptive Thinning Mobility Aware (ATMA) Call Admission Control (CAC) algorithm for
improving the QoS and radio resource utilization of the mobile hotspot networks, which are of critical importance for communicating nodes
in moving wireless networks is proposed. The performance of proposed ATMA CAC scheme is investigated and compare it with the traditional
CAC scheme. The ATMA scheme exploits the mobility events in the highspeed mobility communication environment and the calls (new and
handoff calls) generation pattern to enhance the QoS (new call blocking and
handoff call dropping probabilities) of the mobile users. The numbers of new and
handoff calls in wireless communication networks are dynamic random processes that can be
effectively modeled by the Continuous Furthermore, the NGWNs are envisioned to be Heterogeneous Wireless Networks (HWNs).
The NGWNs are going to be the integration platform of diverse homogeneous wireless communication networks for a convergent
wireless communication network. The HWNs support single and multiple calls (group calls), simultaneously. Decision making is an
integral core of radio resource management. One crucial decision making in HWNs is network selection. Network selection addresses
the problem of how to select the best available access network for a given network user connection. For the integrated platform of
HWNs to be truly seamless and efficient, a robust and stable wireless access network selection algorithm is needed. To meet these
challenges for the different mobile wireless communication network users, the NGWNs will have to provide a great leap in wireless
network capacity, coverage, QoS, and radio resource utilization. Moving wireless communication networks (mobile hotspots) have been
proposed as a solution to providing reliable QoS to high mobility users. In this thesis, an Adaptive Thinning Mobility Aware (ATMA)
Call Admission Control (CAC) algorithm for improving the QoS and radio resource utilization of the mobile hotspot networks, which are
of critical importance for communicating nodes in moving wireless networks is proposed
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