3,522 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
Ultra-Reliable Low-Latency Vehicular Networks: Taming the Age of Information Tail
While the notion of age of information (AoI) has recently emerged as an
important concept for analyzing ultra-reliable low-latency communications
(URLLC), the majority of the existing works have focused on the average AoI
measure. However, an average AoI based design falls short in properly
characterizing the performance of URLLC systems as it cannot account for
extreme events that occur with very low probabilities. In contrast, in this
paper, the main objective is to go beyond the traditional notion of average AoI
by characterizing and optimizing a URLLC system while capturing the AoI tail
distribution. In particular, the problem of vehicles' power minimization while
ensuring stringent latency and reliability constraints in terms of
probabilistic AoI is studied. To this end, a novel and efficient mapping
between both AoI and queue length distributions is proposed. Subsequently,
extreme value theory (EVT) and Lyapunov optimization techniques are adopted to
formulate and solve the problem. Simulation results shows a nearly two-fold
improvement in terms of shortening the tail of the AoI distribution compared to
a baseline whose design is based on the maximum queue length among vehicles,
when the number of vehicular user equipment (VUE) pairs is 80. The results also
show that this performance gain increases significantly as the number of VUE
pairs increases.Comment: Accepted in IEEE GLOBECOM 2018 with 7 pages, 6 figure
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