6G in the sky: On‐demand intelligence at the edge of 3D networks (Invited paper)

Strinati, Emilio Calvanese; Barbarossa, Sergio; Choi, Taesang; Pietrabissa, Antonio; Giuseppi, Alessandro; Santis, Emanuele De; Vidal, Josep; Bečvář, Zdeněk; Haustein, Thomas; Cassiau, Nicolas; Costanzo, Francesca; Kim, Junhyeong; Kim, Ilgyu

doi:10.4218/etrij.2020-0205

Cited by 29 publications

(11 citation statements)

References 46 publications

(54 reference statements)

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“…With 6G, new applications will not be limited to the realm of entertainment and teleconferencing, but more disruptive applications begin to emerge, some of which are life-impacting while others provide alternative solutions for intelligent production and smart mobility with multi-dimensional transportation network consisting of all ground-sea-air-space vehicles with peak mobility up to 1000 km/h (see, for instance, the hyperloop transportation system [26]). This multi-dimension mobility vision opens also the opportunity for Three-Dimensional (3D) native services, enabling end users and machines moving in the 3D space to perceive seamless 6G service support and teleport cloud functionalities on demand, where and when the intelligence support is needed in the 3D space [12]. To this end, KPIs such as localization precision and uniform user experience will be defined in both Two-Dimensional (2D) and 3D space.…”

Section: G Use Cases and Kpismentioning

confidence: 99%

“…Typical applications will include intelligent transportation systems, connected living, super smart cities, etc. • Globally-enhanced Mobile BroadBand (GeMBB) services -This service will expand the computation-oriented communication environment to support rate-hungry applications, such as extended reality services, also in remote locations, such as rural areas [33], oceans, and the sky [12], on demand, i.e. when and where needed.…”

Section: G New Servicesmentioning

confidence: 99%

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6G networks: Beyond Shannon towards semantic and goal-oriented communications

2021

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The goal of this paper is to promote the idea that including semantic and goal-oriented aspects in future 6G networks can produce a significant leap forward in terms of system effectiveness and sustainability. Semantic communication goes beyond the common Shannon paradigm of guaranteeing the correct reception of each single transmitted bit, irrespective of the meaning conveyed by the transmitted bits. The idea is that, whenever communication occurs to convey meaning or to accomplish a goal, what really matters is the impact that the received bits have on the interpretation of the meaning intended by the transmitter or on the accomplishment of a common goal. Focusing on semantic and goal-oriented aspects, and possibly combining them, helps to identify the relevant information, i.e. the information strictly necessary to recover the meaning intended by the transmitter or to accomplish a goal. Combining knowledge representation and reasoning tools with machine learning algorithms paves the way to build semantic learning strategies enabling current machine learning algorithms to achieve better interpretation capabilities and contrast adversarial attacks. 6G semantic networks can bring semantic learning mechanisms at the edge of the network and, at the same time, semantic learning can help 6G networks to improve their efficiency and sustainability.

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Section: G Use Cases and Kpismentioning

confidence: 99%

Section: G New Servicesmentioning

confidence: 99%

6G networks: Beyond Shannon towards semantic and goal-oriented communications

2021

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“…The implementation of an aerial access network (AAN) using NTN including satellites as well as low-and high-altitude platform stations (i.e. LAPS and HAPS) complementing heterogeneous terrestrial networking provides communication, computation, and caching (C3) for the UTM ecosystem [5]. Communication support for UTM ecosystem has three levels, 1) satellites operating at geostationary and low-earth-orbit satellites (GEO/LEO), 2) dedicated ground stations (cellular networks), and 3) Flying ad-hoc networks (FANET) [39] operating in midair as shown in Figure 5.…”

Section: G Communication Support For Utm Ecosystemmentioning

confidence: 99%

“…Hence, 6G is an appropriate technology for UTM systems. Research on UAV and aerial communication is gaining pace by leveraging research advancements in 6G technologies, including edge-cloud computing and machine learning [5]. As soon as 6G is launched and implemented, UTM will adopt 6G for its ecosystem, which might be in the mid-2030s if everything goes right.…”

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confidence: 99%

6G Enabled Unmanned Aerial Vehicle Traffic Management: A Perspective

2021

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Unmanned aerial vehicles (UAVs) and UAV traffic management (UTM) have drawn attention for applications such as parcel delivery, aerial mapping, agriculture, and surveillance based on line-ofsight (LoS) links. UTM is essential to operate multiple fully autonomous UAVs safely beyond the visual line of sight (BVLoS) in the future dense UAV traffic environment. Various research and development teams globally take UTM initiatives and work on platform testing with different industrial partners. In the future, urban airspace will be congested with various types of autonomous aerial vehicles, thereby resulting in complex air-traffic management caused by communication issues. The UTM requires an efficient communication backbone to handle all airborne communication services. Existing cellular networks are suitable only for terrestrial communication and have limitations in supporting aerial communications. These issues motivate the investigation of an appropriate communication technology for advanced UTM systems. Thus, in this study, we present a future perspective of 6G-enabled UTM ecosystems in a very dense and urban air-traffic scenario focusing on non-terrestrial features, including aerial and satellite communication. We also introduce several urban airspace segmentations and discuss a strategic management framework for dynamic airspace traffic management and conflict-free UAV operations. The UTM enhances the adaptive use of the airspace by shaping the airspace with the overall aim of maximizing the capability and efficiency of the network. We also discuss the 6G multi-layer parameters, i.e., space, air, and terrestrial, for safe and efficient urban air transportation in three-dimensional space. Moreover, we discuss the issues and challenges faced by future UTM systems and provide tentative solutions. We subsequently extend the vision of the UTM system and design an advanced and fully autonomous 6G-based UTM system.INDEX TERMS Unmanned Aerial Vehicle, Personalized Aerial Vehicle, UTM system, 6G, traffic management I. INTRODUCTION

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“…The proposed scheme achieved a 12.5% to 60.7% increase in productivity. Also, Calvanese Strinati et al [11] proposed an overview and modeling of the resource allocation of interfered flying devices in the 3D environment. The authors didn't handle the coverage issue of the 6G networks in the 3D environment.…”

Section: A the Literature Of 6g Optimizationmentioning

confidence: 99%

Enhanced Computational Intelligence Algorithm for Coverage Optimization of 6G Non-Terrestrial Networks in 3D Space

et al. 2021

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The next generation 6G communication network is typically characterized by the full connectivity and coverage of Users Equipment (UEs). This leads to the need for moving beyond the traditional twodimensional (2D) coverage service to the three-dimensional (3D) full-service one. The 6G 3D architecture leverages different types of non-terrestrial or aerial nodes that can act as mobile Base Stations (BSs) such as Unmanned Aerial Vehicles (UAVs), Low Altitude Platforms (LAPs), High-Altitude Platform Stations (HAPSs), or even Low Earth Orbit (LEO) satellites. Moreover, aided technologies have been added to the 6G architecture to dynamically increase its coverage efficiency such as the Reconfigurable Intelligent Surfaces (RIS). In this paper, an enhanced Computational Intelligence (CI) algorithm is introduced for optimizing the coverage of UAV-BSs with respect to their location from RIS in the 3D space of 6G architecture. The regarded problem is formulated as a constrained 3D coverage optimization problem. In order to increase the convergence of the proposed algorithm, it is hybridized with a crossover operator. For the validation of the proposed method, it is tested on different scenarios with large-scale coordinates and compared with many recent and hybrid CI algorithms, as Slime Mould Algorithm (SMA), Lévy Flight Distribution (LFD), hybrid Particle Swarm Optimization and Gravitational Search Algorithm (PSOGSA), the Covariance Matrix Adaptation Evolution Strategy (CMA-ES), and hybrid Grey Wolf Optimizer and Cuckoo Search (GWOCS). The experiment and the statistical analysis show the significant efficiency of the proposed algorithm in achieving complete coverage with a lower number of UAV-BSs and without constraints violation.INDEX TERMS 6G technology, computational intelligence, non-terrestrial base stations, reconfigurable intelligent surfaces, three-dimensional coverage optimization problem.

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6G in the sky: On‐demand intelligence at the edge of 3D networks (Invited paper)

Cited by 29 publications

References 46 publications

6G networks: Beyond Shannon towards semantic and goal-oriented communications

6G networks: Beyond Shannon towards semantic and goal-oriented communications

6G Enabled Unmanned Aerial Vehicle Traffic Management: A Perspective

Enhanced Computational Intelligence Algorithm for Coverage Optimization of 6G Non-Terrestrial Networks in 3D Space

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