Testing Facilities for End-to-End Test of Vertical Applications Enabled by 5G Networks: Eindhoven 5G Brainport Testbed

Monroy, Idelfonso Tafur; Raddo, Thiago R.; Rommel, Simon; Okonkwo, Chigo; Calabretta, Nicola; Johannsen, Ulf; Dubbelman, Gijs; Scholtes, J.H.G.; Rutten, Ben

doi:10.1109/icton.2018.8473880

Cited by 11 publications

(13 citation statements)

References 12 publications

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“…The extremely high reliability, the low latency and jitter, opens the possibility to off-load the motion planning tasks to the cloud which can then be directly coordinated by a cloud control system [141]. The 5G based approach is scalable from a resource perspective, to a larger number of drones with only very limited computational abilities, compared with state-of-the art approaches where each drone requires a costly processor [142]. Furthermore, UAV communication networks along with traditional satellite and ground cellular networks construct a space-air-ground heterogeneous network and provide the seamless coverage as well as of improving the capacity for increasingly prosperous IoT networks [121].…”

Section: B Channels Of Uav Applications In Iot and 5gmentioning

confidence: 99%

A Comprehensive Survey on UAV Communication Channel Modeling

Yan¹,

Fu²,

et al. 2019

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Unmanned aerial vehicles (UAVs) have stroke great interested both by the academic community and the industrial community due to their diverse military applications and civilian applications. Furthermore, UAVs are also envisioned to be part of future airspace traffic. The application functions delivery relies on information exchange among UAVs as well as between UAVs and ground stations (GSs), which further closely depends on aeronautical channels. However, there is a paucity of comprehensive surveys on aeronautical channel modeling in line with the specific aeronautical characteristics and scenarios. To fill this gap, this paper focuses on reviewing the air-to-ground (A2G), ground-to-ground (G2G), and air-toair (A2A) channel measurements and modeling for UAV communications and aeronautical communications under various scenarios. We also provide the design guideline for managing the link budget of UAV communications taking account of link losses and channel fading effects. Moreover, we also analyze the receive/transmit diversity gain and spatial multiplexing gain achieved by multiple-antenna-aided UAV communications. Finally, we discuss the remaining challenge and open issues for the future development of UAV communication channel modeling.

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Section: B Channels Of Uav Applications In Iot and 5gmentioning

confidence: 99%

A Comprehensive Survey on UAV Communication Channel Modeling

Yan¹,

Fu²,

et al. 2019

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“…New methods for incremental planning and adjustments of the plans can enhance AVs' adaptability to unexpected scenarios [37]. This could be supplemented with 5G networks to support nearly instantaneous decision-making by providing AVs with more information on nearby obstacles through more reliable vehicle-to-infrastructure (V2X) channels and at much faster speeds than existing 4G networks [133][134][135]. More research into the issues around shared AV service provision is required, where decision-making algorithms require sufficient computing capacity in exploring large decision spaces and catering to "spatiotemporally distributed" bookings in real-time [22].…”

Section: Decision-makingmentioning

confidence: 99%

Algorithmic Decision-Making in AVs: Understanding Ethical and Technical Concerns for Smart Cities

Lim

Taeihagh

2019

Sustainability

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Autonomous Vehicles (AVs) are increasingly embraced around the world to advance smart mobility and more broadly, smart, and sustainable cities. Algorithms form the basis of decision-making in AVs, allowing them to perform driving tasks autonomously, efficiently, and more safely than human drivers and offering various economic, social, and environmental benefits. However, algorithmic decision-making in AVs can also introduce new issues that create new safety risks and perpetuate discrimination. We identify bias, ethics, and perverse incentives as key ethical issues in the AV algorithms' decision-making that can create new safety risks and discriminatory outcomes. Technical issues in the AVs' perception, decision-making and control algorithms, limitations of existing AV testing and verification methods, and cybersecurity vulnerabilities can also undermine the performance of the AV system. This article investigates the ethical and technical concerns surrounding algorithmic decision-making in AVs by exploring how driving decisions can perpetuate discrimination and create new safety risks for the public. We discuss steps taken to address these issues, highlight the existing research gaps and the need to mitigate these issues through the design of AV's algorithms and of policies and regulations to fully realise AVs' benefits for smart and sustainable cities.Sustainability 2019, 11, 5791 2 of 28 surroundings and algorithms that process the data, make, and execute driving decisions through the vehicle's actuators. The quality of data retrieved by the AV's sensors is critical for decision-making [21], and the efficiency, precision and reliability of decision-making algorithms allows AVs to surpass the typical human driver in performing driving tasks [22]. A major component in AVs is machine-learning (ML) [23] algorithms that continuously learn and adapt to new information, which is essential for responding to unexpected situations and providing on-demand transportation services [24]. Algorithms' independence from human input and ML's data-driven nature allows AVs to significantly reduce or eliminate human errors that have been responsible for 90% of road fatalities, such as speeding, alcohol impairment, distractions and induced fear [25,26].However, an overemphasis on technological solutions alone for economic development could risk neglecting social and environmental considerations and thus hinder true "smartness" [27]. Scholars have cautioned against rushing to develop smart mobility solutions such as AVs without being prepared to manage their potential "negative externalities" [1,28]. In particular, issues in algorithmic decision-making in AVs can have undesirable effects on safety and equity. Firstly, data mining processes in AVs are susceptible to biases that lead algorithms to prioritise the safety of certain groups of road users over others and thus, perpetuate discrimination [29,30]. Secondly, many scholars stress the need to design algorithms with ethical considerations to ensure that AVs make ethical driving dec...

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“…This section addresses the integration of different technologies (5G, PON, and VLC) as an elegant alternative network solution to enable autonomous driving solutions, cooperative robotics in smart factories, and open-sky environments with multiple robots/drones interconnected in a centrally controlled network to share common resources and tasks. For example, the proposed integrated network can be useful for addressing cooperative autonomous robots/drones, where ultra-low latency and super-high throughput capabilities must be ensured in a centralized (cloud controlled) manner for highly dynamic and dense environments [18].…”

Section: Technologies Enabling Autonomous Driving and Cooperativementioning

confidence: 99%

“…infrared) and then by using lens is focused on a photodetector (PD) obtaining the electrical data signal, that further is demodulated and decoded by the decoder (in simplest case -microcontroller) [17], [19]. VLC systems are regarded as a promising candidate for V2V and V2I communications in autonomous vehicles networks [18].…”

Section: A Visible Light Communication Technologymentioning

confidence: 99%

“…In the meanwhile, visible light communication (VLC) technology, including light-fidelity (Li-Fi), has recently received considerable attention as an alternative solution for 5G mm-Wave [16]- [18] or as a complimentary technology to be merged with 5G instead of replacing it. This is because VLC/Li-Fi has several interesting benefits such as no frequency license required, free electromagnetic interference, and ease as well as fast deployment.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

The Integration of 5G, PON and VLC Technologies for Ubiquitous Connectivity in Autonomous and Cooperative Systems

Kurbatska

Braunfelds

Bobrovs

et al. 2019

2019 IEEE 2nd 5G World Forum (5GWF)

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DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal. If the publication is distributed under the terms of Article 25fa of the Dutch Copyright Act, indicated by the "Taverne" license above, please follow below link for the End User Agreement:

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Testing Facilities for End-to-End Test of Vertical Applications Enabled by 5G Networks: Eindhoven 5G Brainport Testbed

Cited by 11 publications

References 12 publications

A Comprehensive Survey on UAV Communication Channel Modeling

A Comprehensive Survey on UAV Communication Channel Modeling

Algorithmic Decision-Making in AVs: Understanding Ethical and Technical Concerns for Smart Cities

The Integration of 5G, PON and VLC Technologies for Ubiquitous Connectivity in Autonomous and Cooperative Systems

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