1,619 research outputs found
Maritime coverage enhancement using UAVs coordinated with hybrid satellite-terrestrial networks
Due to the agile maneuverability, unmanned aerial vehicles (UAVs) have shown great promise for on-demand communications. In practice, UAV-aided aerial base stations are not separate. Instead, they rely on existing satellites/terrestrial systems for spectrum sharing and efficient backhaul. In this case, how to coordinate satellites, UAVs and terrestrial systems is still an open issue. In this paper, we deploy UAVs for coverage enhancement of a hybrid satellite-terrestrial maritime communication network. Using a typical composite channel model including both large-scale and small-scale fading, the UAV trajectory and in-flight transmit power are jointly optimized, subject to constraints on UAV kinematics, tolerable interference, backhaul, and the total energy of the UAV for communications. Different from existing studies, only the location-dependent large-scale channel state information (CSI) is assumed available, because it is difficult to obtain the small-scale CSI before takeoff in practice and the ship positions can be obtained via the dedicated maritime Automatic Identification System. The optimization problem is non-convex. We solve it by using problem decomposition, successive convex optimization and bisection searching tools. Simulation results demonstrate that the UAV fits well with existing satellite and terrestrial systems, using the proposed optimization framework
Self-Evolving Integrated Vertical Heterogeneous Networks
6G and beyond networks tend towards fully intelligent and adaptive design in
order to provide better operational agility in maintaining universal wireless
access and supporting a wide range of services and use cases while dealing with
network complexity efficiently. Such enhanced network agility will require
developing a self-evolving capability in designing both the network
architecture and resource management to intelligently utilize resources, reduce
operational costs, and achieve the coveted quality of service (QoS). To enable
this capability, the necessity of considering an integrated vertical
heterogeneous network (VHetNet) architecture appears to be inevitable due to
its high inherent agility. Moreover, employing an intelligent framework is
another crucial requirement for self-evolving networks to deal with real-time
network optimization problems. Hence, in this work, to provide a better insight
on network architecture design in support of self-evolving networks, we
highlight the merits of integrated VHetNet architecture while proposing an
intelligent framework for self-evolving integrated vertical heterogeneous
networks (SEI-VHetNets). The impact of the challenges associated with
SEI-VHetNet architecture, on network management is also studied considering a
generalized network model. Furthermore, the current literature on network
management of integrated VHetNets along with the recent advancements in
artificial intelligence (AI)/machine learning (ML) solutions are discussed.
Accordingly, the core challenges of integrating AI/ML in SEI-VHetNets are
identified. Finally, the potential future research directions for advancing the
autonomous and self-evolving capabilities of SEI-VHetNets are discussed.Comment: 25 pages, 5 figures, 2 table
A Novel Airborne Self-organising Architecture for 5G+ Networks
Network Flying Platforms (NFPs) such as unmanned aerial vehicles, unmanned
balloons or drones flying at low/medium/high altitude can be employed to
enhance network coverage and capacity by deploying a swarm of flying platforms
that implement novel radio resource management techniques. In this paper, we
propose a novel layered architecture where NFPs, of various types and flying at
low/medium/high layers in a swarm of flying platforms, are considered as an
integrated part of the future cellular networks to inject additional capacity
and expand the coverage for exceptional scenarios (sports events, concerts,
etc.) and hard-to-reach areas (rural or sparsely populated areas). Successful
roll-out of the proposed architecture depends on several factors including, but
are not limited to: network optimisation for NFP placement and association,
safety operations of NFP for network/equipment security, and reliability for
NFP transport and control/signaling mechanisms. In this work, we formulate the
optimum placement of NFP at a Lower Layer (LL) by exploiting the airborne
Self-organising Network (SON) features. Our initial simulations show the NFP-LL
can serve more User Equipment (UE)s using this placement technique.Comment: 5 pages, 2 figures, conference paper in IEEE VTC-Fall 2017, in
Proceedings IEEE Vehicular Technology Conference (VTC-Fall 2017), Toronto,
Canada, Sep. 201
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