The profound integration of sensing functionalities is seen as a major step stone towards unleashing the full potential of 6G, yet recent advances in current networks already offer new opportunities for sensing. This is especially true for the mmWave domain which offers a suitable environment for sensing services, e.g. due to the ability to detect and determine the angles of available link opportunities. Whereas previous work devised a fine 3D motion tracking by combining phase measurements along with several co-deployed nodes' links to the mmWave network, this work instead exploits multiple available propagation paths. We observe sub-10 $\mu\mathrm{m}$ 3D motion tracking accuracy for the proposed single user equipment (UE) enhancement, mirroring the conventional multi-UE-based approach performance. However, our detailed error analysis finds that multipath may turn from friend to foe if undesired components are not suppressed sufficiently, as these amplify the effects of phase distortions due to channel noise and hardware imperfections. Our evaluation further yields that the technique is sensitive to erroneous propagation path angle information.
5G mobile communications are bringing a plethora of applications that are challenging existing network infrastructures. These services demand a dynamic, flexible and adaptive infrastructure capable of fulfilling the rigorous requirements they need to operate correctly. Another key point is the need of real-time reactions in the architecture configurations to effectively satisfy changes in the user's behavior. To address these issues, Network Function Virtualization (NFV) and Software-Defined Networking (SDN) paradigms arise as enablers of the network infrastructures of the future. These technologies will permit the design and development of a new set of network applications that will be dynamically managed and orchestrated over multiple domains in an effortless way. In this work, we present an architecture that interconnects two facilities located in Spain and Japan, which permits the deployment of distributed applications. Besides, we detail how the control and data planes are managed to enable the operation of the system.
The introduction of the 5G in the automotive sector paves the way to new business opportunities and stakeholders collaboration, thanks to the availability of new connected vehicles technologies. To emphasise the opportunities of improved data sharing, different business modelling approaches exist, depending on the phase of the data value chain that technologies are able to cover. The 5GMETA open platform aims to leverage CCAM-based captured data to stimulate, facilitate and feed innovative products and services exploring the possibilities enabled by collaborative business models. This paper describes a new business model which focuses on a Use Case (UC) on “Driving Safety and Awareness” that exploit the 5GMETA platform, and highlight its business innovation. In this context, the value proposition relies in the ability to increase road safety thanks to a better driving-misbehaviour detection, thus providing benefits to a wide range of potential stakeholders. The UC has its foundation in the real-time data collected, in a scalable and reliable way, by the platform. The main innovation that the adoption of such business model will bring is the creation of new partnerships that may be enforced by a clear definition of the profit-sharing strategy between the actors involved.
The fifth generation (5G) of mobile communication technology has developed rapidly in recent years. Millimeter wave (mmWave) communication, multi-input-multi-output (MIMO) techniques and beamforming technologies are widely considered for the 5G communication systems. The deployment of 5G networks in most countries is still sparse and real-world 5G signal acquisition is yet difficult and expensive. Therefore, simulation of the 5G environment and signal becomes a critical and vital approach for the research and development in various aspects of 5G wireless networks. The challenge is even more serious in the research of this domain where access to reliable datasets or regenerating simulated data to develop or improve solutions are sometimes extremely difficult processes or impossible. In this paper, we address this gap in the literature by developing a simulator for a 5G environment which considers the design of any urban area and generates beamformed MIMO air interface signals. This simulator is a key step to generate near-realistic data samples (i.e., dataset) which can be further used for various research topics on the 5G. As an example, we use this simulated data for the training of the machine learning models for an indoor positioning use-case scenario. The deterministic three-dimensional raytracing techniques are used to build the simulation model via a commercial software Wireless Insite. This paper describes the structure of the simulator, explains the details of generating and collecting the data samples, and interprets the obtained datasets for indoor localization, as a use-case example. The main goal here is to provide sufficient information and resources to regenerate this dataset for future research works on similar topics.
Network slicing (NS) will be one of the key enablers for 6G systems. NS allows different types of networks to co-exist virtually on the same physical infrastructure in order to support various implementations and verticals. Each type of network slice has features that can support various infrastructure implementations in order to achieve the performance requirements of the different applications without the need for redundant and underutilized infrastructures. As the numbers of verticals and users are increasing very rapidly. automated and fast network slice provisioning becomes necessary. In this paper, the provisioning time for an end-to-end (E2E) network slicing framework is reduced significantly reaching linear scaling in number of slice requests. This is achieved by utilizing techniques from the field of complex networks, namely Dijkstra's and A *. The results show significant reduction in the processing time of the network slicing provisioning as a function of the number of nodes in both the physical infrastructure and the virtual network slices. The results are compared to other techniques.
The 5G Festival is the world's first live immersive hybrid concert, creating an exciting new business model for music professionals, live venues and artists. Exploiting the benefits of 5G technology, such as enhanced mobile broadband and low latency, artists were able to collaborate remotely, from venues 60 miles apart, while audience were able to experience a live event with enhanced immersive experiences. Artists listening to immersive audio were more tolerant to the affects of latency when compared to stereo, which allows for an increase in the distance achievable between the collaborators. During the live performance more than 200 audio channels and 20 video streams were transferred through the three interconnected venues, providing a professional experience to artists and audience alike. This was possible through intelligent network management and use of multicast audio over IP (AoIP) protocols such as AES67/ST2110-30. Finally, a service platform was developed and optimised in relation to latency over the 5G networks resulting in a near ‘real-time’ user experience including additional features such as bit rate optimisation and automatic network reconnection to improve stability and expandable interfaces for live mixing and visual projections.
In this paper, a machine learning-assisted approach is presented for the design of a 3D Printed Metallic Ridge Gap Waveguide-Based array MIMO antenna for inter-cube satellite (CubeSat) communication. The designed antenna has a total dimension of $\boldsymbol{15.5 \times 10.5 \times 5.78} \mathbf{mm}^3$ and is based on aluminum alloy powder (AlSi10Mg) with a conductivity of $\boldsymbol{2.04\times 10^{7}}\ \mathbf{S}/\mathbf{m}$. The antenna exhibits wideband operation in V-band (59.3-66.6 GHz) with a stable realized gain of 10.5 dBi and radiation efficiency of 90% over the operating frequency.
Technical advancements and experimental works for the integration of 5G and Non-Terrestrial Networks (NTN) have gained significant traction over the past few years. NTN components have been officially included in the 5G ecosystem by 3GPP in the latest Release-17. 5G-NTN research is ongoing and it is desirable to have a platform that facilitates quick prototyping of the proof-of-concept methods. OpenAirInterface(OAI) is an open-source experimental yet 3GPP standard-compliant Software Defined Radio (SDR) based protocol stack that has been widely known for implementing 4G/5G technologies. Due to its proven capabilities and flexibility, OAI is currently in the developmental process of integrating adaptations for the 5G-NTN. In this work, we discuss the peculiar features of OAI which are shaping it towards becoming a preferred tool for research and experimentation related to 5G-NTN. We provide details of completed/ongoing 5G-NTN projects leveraging OAI to achieve their objectives. In particular, we discuss 5G-GOA and 5G-LEO where critical adaptations in OAI are being done to support 5G-NTN use-cases. Such adaptations enable direct-access between UE and gNB via transparent payload Geostationary (5G-GOA) and Non-geostationary satellites (5G-LEO). Both projects have closely followed 3GPP discussions over 5G-NTN and the adaptations are compliant with the currently frozen 3GPP Release-17. OAI adaptations from both projects will be merged into the main development branch of OAI. We also provide a future roadmap of OAI towards 5G-NTN development. We believe that the pioneering steps taken in the course of the aforementioned projects will establish OAI as a preferred tool for 5G-NTN research and experimentations.
The network slicing concept divides physical networks into logical networks and abstracts the network resources. With the help of virtualization technologies, these abstracted network resources can be allocated to service providers and resources can dynamically be added to these slices based on users' demands. The infrastructure sharing model with slicing makes it possible for services to lease the resources of the infrastructure provider. This study considers optical network resource allocation from a profit generation perspective with a game, in which service providers bid to lease C-RAN fronthaul paths via auctioning with Vickrey-Clarke-Groves outcomes. The game aims to distribute fronthaul resources with a social-welfare maximizing outcome. Service providers maximize their revenue by predicting user demand and requesting bandwidth resources from the infrastructure provider by bidding in the auction. Users have the option to change their association and switch between the service providers to maximize their utility. The results display that a balanced profit and social welfare trade-off can be achieved in converged optical and mmWave radio networks infrastructure sharing scenario with Vickrey-Dutch auctioning and distributed decision-making.
Network programmability is crucial for addressing the multiplicity and heterogeneity of Network Services, the diversity of the underlying infrastructure of Sixth-Generation (6G) communication systems, and the requirements for maximum efficiency. The programmability of a service platform enables algorithmic network management by leveraging contemporary software virtualization technologies. Moreover, network programmability will abstract the essential network/service and resource configuration, as well as the production and administration of policy lifecycles, as the number of local breakouts (both public and private) is anticipated to grow exponentially. Network programmability is the central point of interest for Hexa-X, the European 6G flagship project, which aims to facilitate the dynamic adaptation to changing network situations and requirements for the most efficient use of available resources. To explore such a critical enabler of futuristic mobile networks, this article addresses the role of network and service programmability and its impact on various aspects of 6G within the context of Hexa-X. In order to accomplish this, the article begins by discussing Hexa-X's proposed service Management and Orchestration (M&O) framework for 6G. Based on this framework, it identifies and explores in greater detail the programmability of four primary processes in 6G: expressing application and service requirements; service description models and profiling; monitoring and diagnostics; and reasoning. Beyond the scope of the Hexa-X, this article aims to serve as a foundation for future research into network and service programmability in 6G.
With the escalating demands for data-intensive content, and the convergence of mobile and connected devices, there is a growing requirement of high bandwidth speeds in multimedia applications. 5G will be a game-changer in the business operations and in providing a engaging customer experience. The 5G vision promises to deliver high-speed downloads with low latency. Managing the exponential growth in data traffic is one of the mobile operator's most challenging issues in 5G networks. Mobile data offloading is a potential and low-cost method for alleviating cellular network congestion. To make this conceivable, we need a new paradigm for hybrid networks that capitalizes on the presence of several alternative communication ways. This entails significant modifications in how data is handled, thereby influencing the behavior of network protocols. This paper presents various techniques for data offloading in cellular 5G networks, discussing the requirements, advantages, and limitations. The research work in this paper provides a detailed presentation of the gaps identified in 5G networks data offloading techniques, the requirements and challenges, and a way forward to solve the challenges, including the most recent technological advancements such as deep learning, edge computing, WiFi-6, social networks and software-defined networks (considering the heterogeneity aspect of the network).
5G has brought many system improvements to both the Radio Access Network and Core Network, with the shift towards a Service-Based Architecture for the Core Network as one of the most significant changes. This paper presents the argumentation for this architectural transformation in the Core Network, combined with the capabilities such change entails and a proposition towards the next steps for Service-Based Architectures towards Release 18 and beyond. Most notably, the domain of Private Networks and stronger inclusion of vertical requirements is the key driver for such continuous transformation, which were demonstrated as a live demo at an European conference and presented in this paper.
The 5G-ROUTES project is part of the European effort to validate, test and pre-deploy 5G connectivity along major transport corridors with a focus on cross-border segments. It addresses Connected and Automated Mobility applications along the ‘Via Baltica North’ traversing Finland, Estonia, and Latvia and, also, 5G connectivity across the Baltic Sea between Finland and Estonia. The signal strength of coastal base stations both in the 700 MHz and 3.5 GHz frequency was measured along the ferry route between the ports of Helsinki/Vuosaari in Finland and Tallinn/Muuga in Estonia. Even though the 5G signals could be detected much further away from the coast than expected, there remains a gap in coverage that needs to be closed to provide continuous 5G connectivity of sufficient bandwidth. The installation of communication infrastructure along water ways is challenging and impossible in some areas, therefore the 5G-ROUTES project has investigated innovative approaches such as various multi-hop concepts and the use of satellites. In the planned trial phase, selected solutions shall be field tested and demonstrated to evaluate their suitability, technical maturity and performance. The obtained results of the 5G-ROUTES ferry trials will be applicable also to much longer ferry routes and can be transferred to road and rail transport in very remote areas where deployment of suitable 5G infrastructure may be technologically challenging and costly.
O-RAN Software Community (OSC) is an open-source project collaborated by O-RAN Alliance and Linux Foundation, aiming to develop reference software components based on 3GPP and O-RAN Alliance specifications. The OSC has twelve projects. Among them, the Integration and Testing (INT) project is responsible for testing the requirements documented in each release for end-to-end and use case testing. Three OSC Community Laboratories were built to speed up the integration and interoperability testing among different projects. This paper summarizes the software components developed by OSC projects and the status of the three OSC Community Laboratories. The activities of each laboratory, how the community collaborates, and the challenges we encountered along the way were elaborated.
This paper presents a security management framework driven by Zero-Touch Network and Service Management (ZSM) paradigm and embedded in the High-Level Architecture (HLA) developed in the INSPIRE-5Gplus project. This project work also included design and implementation of different smart 5G security methods and techniques that are essential for achieving security management in future networks. Moreover, the paper provides a summary of lessons learned and guidelines gathered during the practical validation activities for bringing closed loop and smart security management into Beyond 5G systems. Finally we discuss the key challenges and future work needed to enable integrating closed-loop security management in future networks.
This paper presents field trial results of two combined use cases with different QoS requirements: (1) a transport vertical Smart Junction use case; and (2) a healthcare vertical Paramedic Support use case. We focus on slicing prioritization configured in the RAN, at the gNB level, to guarantee QoS requirements for the combined use cases. We deploy three slices: Transport, Health, and general purpose (Internet) traffic. Our trial results show, by analysing the throughput in the network, that RAN slicing is suitable for guaranteeing QoS requirements of multiple applications and services co-existing in the same 5G network.
To support rigorous and repeatable experimental evaluation of wireless networked systems, the community has made significant efforts to develop experimentation platforms. However, existing platforms primarily focus on the data plane, i.e., the forwarding infrastructure, without explicitly considering the control plane. To fill this gap, in this work we develop NeXT, a software-defined testbed with integrated wireless network simulation, experimentation and optimization capabilities. We first design the data plane, which integrates an event-driven broadband wireless network simulator called UBSim and a software-defined wireless network testing facility called RoboNet. We then design NeXT's control plane, where a software toolchain is developed and deployed to support both traditional model-based optimization and new data-driven control techniques. Finally, we validate the effectiveness of NeXT by considering a series of wireless network optimization and control problems.
The network slicing paradigm allows for partitioning a common network infrastructure into logical networks, i.e. network slices, tailored to specific user intents, including intents for isolation, security or performance reasons. A user may require isolation at different scopes: for the entire network slice, for the network slice subnets or for its composing network functions. Considering the relation between network slicing and Network Function Virtualization (NFV), the intents for isolation need to be mapped to and reflected in the descriptor(s) of network service(s) supporting the network slice(s). However, the network service descriptor (NSD) as defined today cannot capture all the network slice isolation requirements to be enforced during instantiation and at runtime. To overcome some of these limitations we propose extensions to the NSD based on our mapping of different isolation intents of the user to the NSD. We also show how to process the NSD extensions at instantiation and at runtime.
With more subscribers and a variety in business use cases relying on 5G New Radio (NR) network infrastructure, the access network needs to be scalable. The initial network access procedure comprises of users sending preambles to gNB for granting uplink (UL) resources. However, limited preambles in 5G NR can be a bottleneck on the performance of network access procedures. Preamble collisions during initial Random Access Channel (RACH) procedure can limit the scalability of the network. With the increase in the number of cellular User Equipments (UEs) and Machine Type Communication (MTC) devices, the probability of such preamble collisions further increases, thereby leading to reattempts by UEs. This in turn, results in increased latency and reduced channel utilization. In this work, we have used hash functions for selecting preambles during the RACH process. We have used modulo hash functions to convert device identifiers into preamble indexes such that the collision is reduced. In order to counter collisions while using hash functions, we have adopted standard collision resolution techniques such as linear probing, quadratic probing, and double hashing. On performing extensive simulations, it is observed that the hashing based access scheme performs better than the standard Access Class Barring (ACB) scheme in effectively reducing the number of collisions thereby empowering more users to access the network.
