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This paper examines architectural challenges and opportunities arising from Nomadic Networks in the context of emerging 6G research. Nomadic networks are proposed as a solution to the limitations of stationary communication networks, providing enhanced connectivity for dynamic and mobile environments, such as large outdoor events, emergency situations and mobile industrial applications. The key requirements for nomadic networks are outlined, including functional split within the Radio Access Network and robust backhauling solutions. It also addresses the complexity of managing network components, ensuring interoperability with existing systems and maintaining stakeholder trust. A comprehensive architectural framework for Nomadic Networks in 6G is proposed. Different deployment scenarios for Nomadic Networks are investigated, including spawned, steered, and wandering Radio Access Networks as well as integrated, migrated and donated Core Networks. By introducing Nomadic-Network-as-a-Service and a related orchestration framework, the potential for flexible and scalable network management is emphasized. By addressing the architectural challenges, the paper provides a path for the successful implementation of Nomadic Networks towards more adaptable and flexible 6G networks that can meet the evolving needs of multiple sectors., Comment: 7 pages, 2 figures

The emergence of the open radio access network (O-RAN) architecture offers a paradigm shift in cellular network management and service orchestration, leveraging data-driven, intent-based, autonomous, and intelligent solutions. Within O-RAN, the service management and orchestration (SMO) framework plays a pivotal role in managing network functions (NFs), resource allocation, service provisioning, and others. However, the increasing complexity and scale of O-RANs demand autonomous and intelligent models for optimizing SMO operations. To achieve this goal, it is essential to integrate intelligence and automation into the operations of SMO. In this manuscript, we propose three scenarios for integrating machine learning (ML) algorithms into SMO. We then focus on exploring one of the scenarios in which the non-real-time RAN intelligence controller (Non-RT RIC) plays a major role in data collection, as well as model training, deployment, and refinement, by proposing a centralized ML architecture. Finally, we identify potential challenges associated with implementing a centralized ML solution within SMO.

The transforming process in the scope of agriculture towards Smart Agriculture is an essential step to fulfill growing demands in respect to nourishment. Crucial challenges include establishing robust wireless communication in rural areas, enabling collaboration among agricultural machines, and integrating artificial intelligence into farming practices. Addressing these challenges necessitates a consistent communication system, with wireless communication emerging as a key enabler. Cellular technologies, as 5G and its successor 6G, can offer a comprehensive solution here. Leveraging technologies following the ITU-R M. 2160 recommendation like THz communication, low-latency wireless AI, and embedded sensing, can provide a flexible and energy-efficient infrastructure. This paper introduces on-demand networks based on the OpenRAN approach and a 7.2 functional split. By implementing THz front-hauling between components, a flexible application of 5G or future 6G networks can be realized. Experiments demonstrate that THz communication is suitable for data transmission over the eCPRI interface, particularly in terms of data rate, thereby reducing the need for wired alternatives such as fiber optic cables. Furthermore, limitations such as limited range are discussed, and possible initial solutions are presented. The integration of the OpenRAN standard further enhances flexibility, which is crucial in dynamic agricultural environments. This research contributes to the ongoing discourse on the transformative potential of 6G-enabled wireless communication in shaping the future of smart agriculture., Comment: 7 pages, 2 figures

Flexible, self-organizing communication networks will be a key feature in the next mobile communication standard. Network-in-Network (NiN) is one important concept in 6G research, introducing sub-networks tailored to specific application requirements. These sub-networks may be dynamic, i.e., they may appear, disappear, or even move throughout the network. Moreover, sub-networks may operate within a shared frequency spectrum, thereby requiring coordination among them. We demonstrate the concept of Dynamic Spectrum Management (DSM) for future 6G networks that dynamically (re-)allocates spectrum according to active sub-networks in the shared spectrum domain. Resilient control plane connectivity between sub-networks and the DSM is provided by the self-organizing routing protocol KIRA, enabling the aforementioned coordination. This demonstration presents an integrated solution of the DSM concept, providing increased flexibility to support diverse industrial applications and their individual performance requirements simultaneously within the context of a cyber-physical production system (CPPS). For the sub-networks, we use specifically designed hardware for wireless real-time communication and couple them with a network emulation. By switching sub-networks on and off, one can see that the DSM dynamically manages the spectrum allocations for them and that KIRA provides the required connectivity., Comment: 5 pages, 3 figures

The landscape of wireless communication systems is evolving rapidly, with a pivotal role envisioned for dynamic network structures and self-organizing networks in upcoming technologies like the 6G mobile communications standard. This evolution is fueled by the growing demand from diverse sectors, including industry, manufacturing, agriculture, and the public sector, each with increasingly specific requirements. The establishment of non-public networks in the current 5G standard has laid a foundation, enabling independent operation within certain frequencies and local limitations, notably for Internet of Things applications. This paper explores the progression from non-public networks to nomadic non-public networks and their significance in the context of the forthcoming 6G era. Building on existing work in dynamic network structures, non-public networks regulations, and alternative technological solutions, this paper introduces specific use cases enhanced by nomadic networks. In addition, relevant Key Performance Indicators are discussed on the basis of the presented use cases. These serve as a starting point for the definition of requirement clusters and thus for a evaluation metric of nomadic non-public networks. This work lays the groundwork for understanding the potential of nomadic non-public networks in the dynamic landscape of 6G wireless communication systems., Comment: 8 pages, 1 figure

Open-radio access network (O-RAN) seeks to establish principles of openness, programmability, automation, intelligence, and hardware-software disaggregation with interoperable interfaces. It advocates for multi-vendorism and multi-stakeholderism within a cloudified and virtualized wireless infrastructure, aimed at enhancing the deployment, operation, and maintenance of RAN architecture. This enhancement promises increased flexibility, performance optimization, service innovation, energy efficiency, and cost efficiency in fifth-generation (5G), sixth-generation (6G), and future networks. One of the key features of the O-RAN architecture is its support for network slicing, which entails interaction with other slicing domains within a mobile network, notably the transport network (TN) domain and the core network (CN) domain, to realize end-to-end (E2E) network slicing. The study of this feature requires exploring the stances and contributions of diverse standards development organizations (SDOs). In this context, we note that despite the ongoing industrial deployments and standardization efforts, the research and standardization communities have yet to comprehensively address network slicing in O-RAN. To address this gap, this survey paper provides a comprehensive exploration of network slicing in O-RAN through an in-depth review of specification documents from O-RAN Alliance and research papers from leading industry and academic institutions. The paper commences with an overview of the ongoing standardization efforts and open-source contributions associated with O-RAN, subsequently delving into the latest O-RAN architecture with an emphasis on its slicing aspects. Further, the paper explores deployment scenarios for network slicing within O-RAN, examining options for the deployment and orchestration of O-RAN and TN network slice subnets..., Comment: 45 pages, 12 figures, 4 tables, submitted to the IEEE for possible publication

Federated learning (FL) offers a privacy-preserving collaborative approach for training models in wireless networks, with channel estimation emerging as a promising application. Despite extensive studies on FL-empowered channel estimation, the security concerns associated with FL require meticulous attention. In a scenario where small base stations (SBSs) serve as local models trained on cached data, and a macro base station (MBS) functions as the global model setting, an attacker can exploit the vulnerability of FL, launching attacks with various adversarial attacks or deployment tactics. In this paper, we analyze such vulnerabilities, corresponding solutions were brought forth, and validated through simulation., Comment: Submitted to IEEE GLOBECOM 2024

The relevance of studies in queuing theory in social systems has inspired its adoption in other mainstream technologies with its application in distributed and communication systems becoming an intense research domain. Considerable work has been done regarding the application of the impatient queuing phenomenon in distributed computing to achieve optimal resource sharing and allocation for performance improvement. Generally, there are two types of common impatient queuing behaviour that have been well studied, namely balking and reneging, respectively. In this survey, we are interested in the third type of impatience: jockeying, a phenomenon that draws origins from impatient customers switching from one queue to another. This survey chronicles classical and latest efforts that labor to model and exploit the jockeying behaviour in queuing systems, with a special focus on those related to information and communication systems, especially in the context of Multi-Access Edge Computing. We comparatively summarize the reviewed literature regarding their methodologies, invoked models, and use cases., Comment: Submitted to ACM Computing Surveys

Use-case-specific network slicing in decentralized multi-tenancy cloud environments is a promising approach to bridge the gap between the demand and supply of resources in next-generation communication networks. Our findings associate different slice profiles to queues in a multi-server setting, such that tenants continuously assess their preferences and make rational decisions to minimize the queuing delay. Deviated from classical approaches that statistically model the jockeying phenomena in queuing systems, our work pioneers to setup a behavioral model of jockeying impatient tenants. This will serve as a basis for decentralized management of multi-queue systems, where the decision to jockey is individually made by each tenant upon its up-to-date assessment of expected waiting time. Additionally, we carry out numerical simulations to empirically unravel the parametric dependencies of the tenants' jockeying behavior., Comment: To appear in IEEE MetidCom 2024

Sensing plays a crucial role in autonomous and assisted vehicular driving, as well as in the operation of autonomous drones. The traditional segregation of communication and onboard sensing systems in mobility applications is due to be merged using Joint Communication and Sensing (JCAS) in the development of the 6G mobile radio standard. The integration of JCAS functions into the future road traffic landscape introduces novel challenges for the design of the 6G system architecture. Special emphasis will be placed on facilitating direct communication between road users and aerial drones. In various mobility scenarios, diverse levels of integration will be explored, ranging from leveraging communication capabilities to coordinate different radars to achieving deep integration through a unified waveform. In this paper, we have identified use cases and derive five higher-level Tech Cases (TCs). Technical and functional requirements for the 6G system architecture for a device-oriented JCAS approach will be extracted from the TCs and used to conceptualize the architectural views., Comment: 6 pages, 3 figures, 4th IEEE Symposium on Joint Communication and Sensing

The paper proposes a framework to identify and avoid the coverage hole in an indoor industry environment. We assume an edge cloud co-located controller that followers the Automated Guided Vehicle (AGV) movement on a factory floor over a wireless channel. The coverage holes are caused due to blockage, path-loss, and fading effects. An AGV in the coverage hole may lose connectivity to the edge-cloud and become unstable. To avoid connectivity loss, we proposed a framework that identifies the position of coverage hole using a Support- Vector Machine (SVM) classifier model and constructs a binary coverage hole map incorporating the AGV trajectory re-planning to avoid the identified coverage hole. The AGV's re-planned trajectory is optimized and selected to avoid coverage hole the shortest coverage-hole-free trajectory. We further investigated the look-ahead time's impact on the AGV's re-planned trajectory performance. The results reveal that an AGV's re-planned trajectory can be shorter and further optimized if the coverage hole position is known ahead of time, Comment: IEEE copyright

This paper addresses the challenges of mobile user requirements in shadowing and multi-fading environments, focusing on the Downlink (DL) radio node selection based on Uplink (UL) channel estimation. One of the key issues tackled in this research is the prediction performance in scenarios where estimated channels are integrated. An adaptive deep learning approach is proposed to improve performance, offering a compelling alternative to traditional interpolation techniques for air-to-ground link selection on demand. Moreover, our study considers a 3D channel model, which provides a more realistic and accurate representation than 2D models, particularly in the context of 3D network node distributions. This consideration becomes crucial in addressing the complex multipath fading effects within geometric stochastic 3D 3GPP channel models in urban environments. Furthermore, our research emphasises the need for adaptive prediction mechanisms that carefully balance the trade-off between DL link forecasted frequency response accuracy and the complexity requirements associated with estimation and prediction. This paper contributes to advancing 3D radio resource management by addressing these challenges, enabling more efficient and reliable communication for energy-constrained flying network nodes in dynamic environments., Comment: This work has been submitted to the IEEE conference for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible

Underlayer networks in the context of 6G for manufacturing are crucial. They address the evolving needs of highly interconnected and autonomous systems in industry. The digitalization of manufacturing processes, driven by the Internet of Things and increased data availability, enables more efficient and demand-driven production. However, wireless connectivity, which offers flexibility and easy integration of components, comes with challenges such as signal interference or high latency. A new management system is needed to coordinate and route traffic of multiple networks in a specific coverage area. This paper proposes underlayer networks designed for manufacturing, providing low latency, reliability, and security. These networks enable wireless connectivity and integration of wireless technologies into the manufacturing environment, enhancing flexibility and efficiency. The paper also discusses network slicing, spectrum sharing, and the limitations of current wireless networks in manufacturing. It introduces a network concept for underlayer networks and evaluates its application in closed-loop communication for machine tools. The study concludes with future research prospects in this area.

The emerging fifth generation (5G) and the upcoming sixth generation (6G) communication technologies introduce the use of space- and airborne networks in their architectures under the scope of non-terrestrial networks (NTNs). With this integration of satellite and aerial platform networks, better coverage, network flexibility and easier deployment can be achieved. Correspondingly, satellite broadband internet providers have launched an increasing number of small satellites operating in low earth orbit (LEO). These recent developments imply an increased electromagnetic field (EMF) exposure to humans and the environment. In this work, we provide a short overview of the state of consumer-grade satellite networks including broadband satellites and future NTN services. We also consider the regulatory state governing their operation within the context of EMF exposure. Finally, we highlight the aspects that are relevant to the assessment of EMF exposure in relation to NTNs., Comment: to be listed in the proceedings of IEEE International Conference on Mobile Ad-Hoc and Smart Systems (MASS) 2023

The advent of 5G New Radio (NR) technology has revolutionized the landscape of wireless communication, offering various enhancements such as elevated system capacity, improved spectrum efficiency, and higher data transmission rates. To achieve these benefits, 5G has implemented the Ultra-Dense Network (UDN) architecture, characterized by the deployment of numerous small general Node B (gNB) units. While this approach boosts system capacity and frequency reuse, it also raises concerns such as increased signal interference, longer handover times, and higher handover failure rates. To address these challenges, the critical factor of Time to Trigger (TTT) in handover management must be accurately determined. Furthermore, the density of gNBs has a significant impact on handover performance. This study provides a comprehensive analysis of 5G handover management. Through the development and utilization of a downlink system-level simulator, the effects of various TTT values and gNB densities on 5G handover were evaluated, taking into consideration the movement of Traffic Users (TUs) with varying velocities. Simulation results showed that the handover performance can be optimized by adjusting the TTT under different gNB densities, providing valuable insights into the proper selection of TTT, UDN, and TU velocity to enhance 5G handover performance., Comment: 6 pages, 6 figures, Eucnc 2023 Gothenburg, Sweden. arXiv admin note: text overlap with arXiv:2301.08053

The introduction of new types of frequency spectrum in 6G technology facilitates the convergence of conventional mobile communications and radar functions. Thus, the mobile network itself becomes a versatile sensor system. This enables mobile network operators to offer a sensing service in addition to conventional data and telephony services. The potential benefits are expected to accrue to various stakeholders, including individuals, the environment, and society in general. The paper discusses technological development, possible integration, and use cases, as well as future development areas.

With technology and societal development, the 5th generation wireless communication (5G) contributes significantly to different societies like industries or academies. Vehicle-to-Everything (V2X) communication technology has been one of the leading services for 5G which has been applied in vehicles. It is used to exchange their status information with other traffic and traffic participants to increase traffic safety and efficiency. Cellular-V2X (C-V2X) is one of the emerging technologies to enable V2X communications. The first Long-Term Evolution (LTE) based C-V2X was released on the 3rd Generation Partnership Project (3GPP) standard. 3GPP is working towards the development of New Radio (NR) systems that it is called 5G NR V2X. One single numerology in LTE cannot satisfy most performance requirements because of the variety of deployment options and scenarios. For this reason, in order to meet the diverse requirements, the 5G NR Physical Layer (PHY) is designed to provide a highly flexible framework. Scalable Orthogonal Frequency-Division Multiplexing (OFDM) numerologies make flexibility possible. The term numerology refers to the PHY waveform parametrization and allows different Subcarrier Spacings (SCSs), symbols, and slot duration. This paper implements the Link-Level (LL) simulations of LTE C-V2X communication and 5G NR V2X communication where simulation results are used to compare similarities and differences between LTE and 5G NR. We detect the effect of variable PHY Numerologies of 5G NR on the LL performance of V2X. The simulation results show that the performance of 5G NR improved by using variable numerologies., Comment: 6 pages, 5 figures, ICCC 2022

Instantaneous measurements of the electromagnetic field (EMF) strength do not reflect the maximum exposure levels possible in a given location. An extrapolation factor needs to be applied to the measurements before comparing them against the local exposure guidelines or recommendations for compliance evaluation. For the fifth generation (5G) networks, a standardized approach for extrapolating EMF values is yet to be defined. This work provides an overview of the state-of-the-art research that focuses on estimating the maximum EMF exposure caused by radiation from 5G base stations. It also considers current efforts by national and international organizations to establish standardized methods for extrapolating the EMF measurements which is necessary in investigating conformance with the EMF guidelines and regulations., Comment: This is a preprint version, the full paper has been accepted by the IEEE Conference on Standards for Communications and Networking (CSCN), Thessaloniki, Greece. November 2022

As cellular networks evolve towards the 6th generation, machine learning is seen as a key enabling technology to improve the capabilities of the network. Machine learning provides a methodology for predictive systems, which can make networks become proactive. This proactive behavior of the network can be leveraged to sustain, for example, a specific quality of service requirement. With predictive quality of service, a wide variety of new use cases, both safety- and entertainment-related, are emerging, especially in the automotive sector. Therefore, in this work, we consider maximum throughput prediction enhancing, for example, streaming or high-definition mapping applications. We discuss the entire machine learning workflow highlighting less regarded aspects such as the detailed sampling procedures, the in-depth analysis of the dataset characteristics, the effects of splits in the provided results, and the data availability. Reliable machine learning models need to face a lot of challenges during their lifecycle. We highlight how confidence can be built on machine learning technologies by better understanding the underlying characteristics of the collected data. We discuss feature engineering and the effects of different splits for the training processes, showcasing that random splits might overestimate performance by more than twofold. Moreover, we investigate diverse sets of input features, where network information proved to be most effective, cutting the error by half. Part of our contribution is the validation of multiple machine learning models within diverse scenarios. We also use explainable AI to show that machine learning can learn underlying principles of wireless networks without being explicitly programmed. Our data is collected from a deployed network that was under full control of the measurement team and covered different vehicular scenarios and radio environments., Comment: 18 pages, 12 Figures. Accepted on IEEE Access

In 5G wireless communication, Intelligent Transportation Systems (ITS) and automobile applications, such as autonomous driving, are widely examined. These applications have strict requirements and often require high Quality of Service (QoS). In an urban setting, Ultra-Dense Networks (UDNs) have the potential to not only provide optimal QoS but also increase system capacity and frequency reuse. However, the current architecture of 5G UDN of dense Small Cell Nodes (SCNs) deployment prompts increased delay, handover times, and handover failures. In this paper, we propose a Machine Learning (ML) supported Mobility Prediction (MP) strategy to predict future Vehicle User Equipment (VUE) mobility and handover locations. The primary aim of the proposed methodology is to minimize Unnecessary Handover (UHO) while ensuring VUEs take full advantage of the deployed UDN. We evaluate and validate our approach on a downlink system-level simulator. We predict mobility using Support Vector Machine (SVM), Decision Tree Classifier (DTC), and Random Forest Classifier (RFC). The simulation results show an average reduction of 30% in handover times by utilizing ML-based MP, with RFC showing the most reduction up to 70% in some cases., Comment: 6 pages, 5 figures, VNC conference

With wireless communication technology development, the 5G New Radio (NR) has been proposed and developed for a decade. This advanced mobile communication technology has more advancements, such as higher system capacity, higher spectrum efficiency, higher data rates, and so on. In 5G, Ultra- Dense Network (UDN) is deployed for increasing the system capacity and frequency reuse to meet high application requirements. The architecture of 5G UDN is to realize the dense and flexible deployment of smaller general Node B (gNB). However, the increased capacity of applying UDN in 5G is anticipated at the cost of increased signal interference, increased handover times, and increased handover failures. The Time to Trigger (TTT) is one of the most important factors in handover frequency which is deserved to be detected. Moreover, the density of the 5G gNBs influences the handover times and performance as well. In this work, we provide a compendium of 5G handover management. A downlink system-level simulator for 5G handover is built and utilized to evaluate the effect of different TTT values and densities of gNBs on the 5G handover. In addition, different velocities of Traffic Users (TUs) have been applied to the simulation system. From the simulation results, the handover performance has been analyzed and optimized by applying adjustable TTT under different densities of gNBs which will help people have a better understanding of the selection and effect of proper TTT, UDN, and different velocities of TUs on 5G handover performance., Comment: 6 pages, 6 figures

The evolution of wireless communications into 6G and beyond is expected to rely on new machine learning (ML)-based capabilities. These can enable proactive decisions and actions from wireless-network components to sustain quality-of-service (QoS) and user experience. Moreover, new use cases in the area of vehicular and industrial communications will emerge. Specifically in the area of vehicle communication, vehicle-to-everything (V2X) schemes will benefit strongly from such advances. With this in mind, we have conducted a detailed measurement campaign that paves the way to a plethora of diverse ML-based studies. The resulting datasets offer GPS-located wireless measurements across diverse urban environments for both cellular (with two different operators) and sidelink radio access technologies, thus enabling a variety of different studies towards V2X. The datasets are labeled and sampled with a high time resolution. Furthermore, we make the data publicly available with all the necessary information to support the onboarding of new researchers. We provide an initial analysis of the data showing some of the challenges that ML needs to overcome and the features that ML can leverage, as well as some hints at potential research studies., Comment: 5 pages, 6 figures. Accepted for presentation at IEEE conference VTC2023-Spring. Available dataset at https://ieee-dataport.org/open-access/berlin-v2x

5G promises to shift Industry 4.0 to the next level by allowing flexible production. However, many communication standards are used throughout a production site, which will stay so in the foreseeable future. Furthermore, localization of assets will be equally valuable in order to get to a higher level of automation. This paper proposes a reference architecture for a convergent localization and communication network for smart manufacturing that combines 5G with other existing technologies and focuses on high-mix low-volume application, in particular at small and medium-sized enterprises. The architecture is derived from a set of functional requirements, and we describe different views on this architecture to show how the requirements can be fulfilled. It connects private and public mobile networks with local networking technologies to achieve a flexible setup addressing many industrial use cases., Comment: 10 pages; submitted to 6th International Conference on System-Integrated Intelligence. Intelligent, flexible and connected systems in products and production, 7-9 September Genova, Italy

Live migration of services is a prerequisite for various use cases that must be fulfilled for the realization of Industry 4.0. In addition, many different types of services need to provide mobility and consequently need to be migrated live. These can be offloaded algorithms from mobile devices, such as unmanned vehicles or robots, security services, communication services or classic control tasks. In particular, the latter place very high demands on determinism and latency. Here, it is of utmost importance that the downtime of the service is as low as possible. Since existing live migration approaches try to optimize multiple metrics such as downtime, migration time as well as energy consumption, which are equally relevant in the IT domain, it is not possible to use any of these approaches without adoptions. Therefore, a novel concept is proposed that builds on top of both existing migration approaches as well as virtualization technologies and aims primarily at minimizing service downtime. Furthermore, the concept is evaluated using a test environment. The results show that a sub-millisecond downtime can be achieved with the proposed concept. Moreover, the total migration time is in the range of several hundred milliseconds for the highest performance setting and two seconds for a non-invasive approach.

Future Industrial 4.0 applications in the 6G era is calling for high dependability that goes far beyond the current ultra-reliable low latency communication (URLLC), and therewith proposed critical challenges to the communication technology. Instead of struggling against the physical and technical limits towards an extreme URLLC (xURLLC), communication-control co-design (CoCoCo) appears a more promising solution. This work proposes a novel framework of CoCoCo, which is not only enhancing the dependability of 6G industrial applications such as remote control, but also exhibiting rich potential in revolutionizing the future industry per openness and flexibility of manufacturing systems., Comment: To appear in the 22nd IEEE International Conference on Software Quality, Reliability, and Security (QRS 2022) Workshops

This article reveals an adequate comprehension of basic defense, security challenges, 2 and attack vectors in deploying multi-network slicing. Network slicing is a revolutionary concept 3 of providing mobile network on-demand and expanding mobile networking business and services 4 to a new era. The new business paradigm and service opportunities are encouraging vertical 5 industries to join and develop their own mobile network capabilities for enhanced performances 6 that are coherent with their applications. However, a number of security concerns are also raised 7 in this new era. In this article, we focus on the deployment of multi-network slicing with multi8 tenancy. We identify the security concerns, and discuss about the defense approaches such as 9 network slice isolation and insulation in a multi-layer network slicing security model. Also, we 10 identify the importance to appropriately select the network slice isolation points, and propose 11 a generic framework to optimize the isolation policy regarding the implementation cost while 12 guaranteeing the security and performance requirements., Comment: Accepted by MDPI Network on 03.03.2022 for publication

Nowadays mobile communication is growing fast in the 5G communication industry. With the increasing capacity requirements and requirements for quality of experience, mobility prediction has been widely applied to mobile communication and has becoming one of the key enablers that utilizes historical traffic information to predict future locations of traffic users, Since accurate mobility prediction can help enable efficient radio resource management, assist route planning, guide vehicle dispatching, or mitigate traffic congestion. However, mobility prediction is a challenging problem due to the complicated traffic network. In the past few years, plenty of researches have been done in this area, including Non-Machine-Learning (Non-ML)- based and Machine-Learning (ML)-based mobility prediction. In this paper, firstly we introduce the state of the art technologies for mobility prediction. Then, we selected Support Vector Machine (SVM) algorithm, the ML algorithm for practical traffic date training. Lastly, we analyse the simulation results for mobility prediction and introduce a future work plan where mobility prediction will be applied for improving mobile communication., Comment: 5 pages, 7 figures, MKT'21 osnabruck

In the context of Industry 4.0, more and more mobile use cases are appearing on industrial factory floors. These use cases place high demands on various quantitative requirements, such as latency, availability, and more. In addition, qualitative requirements such as flexibility are arising. Since virtualization technology is a key enabler for the flexibility that is required by novel use cases and on the way to organic networking as it is addressed by 6G, we investigate container virtualization technology in this paper. We focus on container technology since OS-level virtualization has multiple benefits compared to hardware virtualization, such as VMs. Thus, we discuss several aspects of container based virtualization, e.g. selection of suitable network drivers and orchestration tools, with respect to most important 5GC functions. In addition, the functions have different quantitative or qualitative requirements depending on whether they are stateless or stateful, and whether the specific function is located at either the control or user plane. Therefore, we also analyze the aforementioned live migration concepts for the 5GC functions and evaluate them based on well-defined metrics, such as migration time and process downtime.

Smart manufacturing has the objective of creating highly flexible and resource optimized industrial plants. Furthermore, the improvement of product quality is another important target. These requirements implicate more complex control algo-rithms. Processing these algorithms may exceed the capabilities of resource constrained devices, such as programmable logic controllers (PLCs). In this case, the necessity for computation offloading is given. Due to the fact that industrial plants are currently designed for a life-cycle-time of more than ten years, in a realistic smart manufacturing scenario, these devices have to be considered. Therefore, we investigate the impact of complex algorithms on conventional PLCs by simulating them with a load generator. In addition, we propose a realistic factory scenario including benchmarks for both wireline and wireless communication systems. Thus, their round-trip time (RTT) is measured with and without additional load on the network. With the help of these investigations, break-even points for the application of computation offloading of two typical PLCs of Siemens S7 series can be calculated.

Realizing the industrial Internet of Things, more andmore mobile use cases will emerge in the industrial landscape,requiring both novel concepts and smooth integration into legacydeployments.Since accurate time synchronization is particularly challengingfor wireless devices, we propose a concept for simple but accuratesynchronization in IEEE 802.11 wireless local area network thatextends the Reference Broadcast Infrastructure Synchronizationprotocol, and a suitable integration of IEEE 802.1AS that is partof the IEEE time-sensitive networking standards. In addition,the concept is evaluated with a testbed using commercial off-the-shelf hardware and a realistic discrete automation demonstratorequipped mostly with industrial components. By using the afore-mentioned devices for wireless communications, this concept canbe directly applied in existing industrial solutions, thus achievingthe proposed results. It is shown that the achieved synchronicity issuitable for a wide range of mandatory mobile use cases, which aremost important for a fully functional industrial Internet of Things.

Multi-access edge computing (MEC) emerges as an essential part of the upcoming Fifth Generation (5G) and future beyond-5G mobile communication systems. It adds computational power towards the edge of cellular networks, much closer to energy-constrained user devices, and therewith allows the users to offload tasks to the edge computing nodes for low-latency applications with very-limited battery consumption. However, due to the high dynamics of user demand and server load, task congestion may occur at the edge nodes resulting in long queuing delay. Such delays can significantly degrade the quality of experience (QoE) of some latency-sensitive applications, raise the risk of service outage, and cannot be efficiently resolved by conventional queue management solutions. In this article, we study a latency-outage critical scenario, where users intend to limit the risk of latency outage. We propose an impatience-based queuing strategy for such users to intelligently choose between MEC offloading and local computation, allowing them to rationally renege from the task queue. The proposed approach is demonstrated by numerical simulations to be efficient for generic service model, when a perfect queue status information is available. For the practical case where the users obtain only imperfect queue status information, we design an optimal online learning strategy to enable its application in Poisson service scenarios., Comment: To appear in IEEE Transactions on Wireless Communications

There are a large number of vertical industries implementing multiple use cases, each use case characterized by diverging service, network, and connectivity requirements such as automobile, manufacturing, power grid, etc. Such heterogeneity cannot be effectively managed and efficiently mapped onto a single type of network slice instance (NSI). Thus the tailored provisioning of an end-to-end network slicing solution to a vertical industry that consists of multiple use cases is a critical issue, which motivates this article, aimed at exploring this never-addressed and challenging research problem by proposing the Use-case Specific Network Slicing and the SubNetwork Slicing concepts that enable the provisioning of Use-case-specific NSI(US-NSI) and GeNeric NSI(GN-NSI), respectively. Both approaches tackle the same technical issue of provisioning, management, and orchestration of per vertical per use case NSIs in order to improve resource allocation and enhance network performance. The article also presents the architectural frameworks for managing US-NSI and GN-NSI, which extend the service deployment concept and system architecture of network slicing for vertical customers of fifth-generation (5G) mobile networks.

In order to cope with the explosive growth of data traffic which is associated with a wide plethora of emerging applications and services that are expected to be used by both ordinary users and vertical industries, the congestion control mechanism is considered to be vital. In this paper, we proposed a congestion control mechanism that could function within the framework of Multi-Access Edge Computing (MEC). The proposed mechanism is aiming to make real-time decisions for selectively buffering traffic while taking network condition and Quality of Service (QoS) into consideration. In order to support a MEC-assisted scheme, the MEC server is expected to locally store delay-tolerant data traffics until the delay conditions expire. This enables the network to have better control over the radio resource provisioning of higher priority data. To achieve this, we introduced a dedicated function known as Congestion Control Engine (CCE), which can capture Radio Access Network (RAN) condition through Radio Network Information Service (RNIS) function, and use this knowledge to make the real-time decision for selectively offloading traffic so that it can perform more intelligently. Analytical evaluation results of our proposed mechanism confirm that it can alleviate network congestion more efficiently., Comment: This paper presented in International Symposium on Wireless Communication Systems (ISWCS 2018)

With a wide deployment of Multi-Access Edge Computing (MEC) in the Fifth Generation (5G) mobile networks, virtual network functions (VNF) can be flexibly migrated between difference locations, and therewith significantly enhances the network resilience to counter the degradation in quality of service (QoS) due to network function outages. A balance has to be taken carefully, between the loss reduced by VNF migration and the operations cost generated thereby. To achieve this in practical scenarios with realistic user behavior, it calls for models of both cost and user mobility. This paper proposes a novel cost model and a AI-empowered approach for a rational migration of stateful VNFs, which minimizes the sum of operations cost and potential loss caused by outages, and is capable to deal with the complex realistic user mobility patterns., Comment: Accepted by the IEEE WCNC 2021 Workshop on Intelligent Computing and Caching at the Network Edge

Industry 4.0 offers many possibilities for creating highly efficient and flexible manufacturing. To create such advantages, highly automated and thus digitized processes and systems are required. Here, most technologies known from the office floor are basically suitable for these tasks, but cannot meet the high demands of industrial use cases. Therefore, they cannot replace industrial technologies and devices that have performed well over decades "out of the box". For this reason, many technologies known from the office floor are being investigated and adapted for industrial environments. An important task is the virtualization of process controls, as more and more devices use computation offloading, e.g. due to limited resources. In this paper we extend the work on our novel architecture that enables numerous use cases and meets industrial requirements by virtualizing process controllers. In addition, a testbed based on a factory scenario is proposed to evaluate the most important features of the presented architecture.

As of today, 5G mobile systems have been already widely rolled out, it is the right time for academia and industry to explore the next generation mobile communication system beyond 5G. To this end, this paper provides an abstracted survey for the 6G mobile system. We shed light on the key driving factors for 6G through predicting the growth trend of mobile traffic and mobile service subscriptions until the year of 2030, envisioning the potential use cases and applications, as well as deriving the potential use scenarios. Then, a number of key performance indicators to support the 6G use cases are identified and their target values are estimated in a quantitatively manner, which is compared with those of 5G clearly in a visualized way. An investigation of the efforts spent on 6G research in different countries and institutions until now is summarized, and a potential roadmap in terms of the definition, specification, standardization, and spectrum regulation is given. Finally, an introduction to potential key 6G technologies is provided. The principle, technical advantages, challenges, and open research issues for each identified technology are discussed.

The digitalization of manufacturing processes is leading to a highly increased amount of connected devices. In the course of this development a process was developed and implemented, which optimizes IEEE 802.11-systems relating to the interference situation by using context-information. This was realized by division into two fields. First of all, data providers calculate their own interference situation to determine the optimal frequency out of the ascertained data. In this case optimal means that the chosen channel should have the lowest interference power. In a second step these providers also calculating the interference information about all Service Set Identifier (SSID) in range. The measured data is then divided into the allowed radio channel. Afterwards the gathered information will be transferred to a central space. An already existing infrastructure is used as a initial point for the further process. As soon as the provider has transferred new data, a broker can inform connected users that there is an update in the inference situation. With this developed architecture an approach to face the hidden node problem is given. Additional a system for safety-critical information is implemented., Comment: conferene, interference situation, context-information, context-awareness, 802.11n, medium access control, spectrum management

Industry 4.0 describes an adaptive and changeable production, where its factory cells have to be reconfigured at very short intervals, e.g. after each workpiece. Furthermore, this scenario cannot be realized with traditional devices, such as programmable logic controllers. Here the use of well-proven technologies of the information technology are conquering the production hall (IT-OT convergence). Therefore, both virtualization and novel communication technologies are being introduced in the field of industrial automation. In addition, these technologies are seen as the key for facilitating various emerging use cases. However, it is not yet clear whether each of the dedicated hardware and software components, which have been developed for specific control tasks and have performed well over decades, can be upgraded without major adjustments. In this paper, we examine the opportunities and challenges of hardware and operating system-level virtualization based on the stringent requirements imposed by industrial applications. For that purpose, benchmarks for different virtualization technologies are set by determining their computational and networking overhead, configuration effort, accessibility, scalability, and security.

The term Industry 4.0, which refers to the fourth industrial revolution, aims at the digitalization of industries, including all kinds of production assets. With the help of these, so-called industrial cyber-physical systems, which form the industrial Internet of Things, numerous novel use cases that are key enabler for a smart manufacturing, can be realized. However, existing facilities mainly consist of legacy equipment and technologies that do not offer these kind of flexibility. To address this issue, we introduce an architecture that allows a flexible reconfiguration and redeployment of future process control systems. Moreover, a high system availability and reliability, as required by industrial applications, has been taken into account. The architectural design follows the 4+1 model approach as it is available in the literature. This ensures, that the design results in a holistic architecture. Additionally, we provide insights into first results and outline future development steps.

Industry 4.0 brings up new types of use cases, whereby mobile use cases play a significant role. These use cases have stringent requirements on both automation and communication systems that cannot be achieved with recent shop floor technologies. Therefore, novel technologies such as IEEE time-sensitive networking (TSN) and Open Platform Communications Unified Architecture (OPC UA) are being introduced. In addition, for the realization of mobile use cases, wireline technologies cannot be used and have to be replaced by wireless connections, which have to meet the high demands of the industrial landscape. Here, 5th generation wireless communication system (5G) is seen as a promising candidate. Especially encouraging and similarly challenging is the cooperative work of mobile robots, where particularly high demands on time synchronization arise. Therefore, this paper introduces a concept for the integration of TSN time synchronization (IEEE 802.1AS) conform with 5G to fulfill the requirements of these use cases. Furthermore, the paper describes a testbed for discrete manufacturing, consisting pre-dominantly of industrial equipment, in order to evaluate the presented approach.

DevOps describes a method to reorganize the way different disciplines in software engineering work together to speed up software delivery. However, the introduction of DevOps-methods to organisations is a complex task. A successful introduction results in a set of structured process descriptions. Despite the structure, this process leaves margin for error: Especially security issues are addressed in individual stages, without consideration of the interdependence. Furthermore, applying DevOps-methods to distributed entities, such as the Internet of Things (IoT) is difficult as the architecture is tailormade for desktop and cloud resources. In this work, an overview of tooling employed in the stages of DevOps processes is introduced. Gaps in terms of security or applicability to the IoT are derived. Based on these gaps, solutions that are being developed in the course of the research project SCRATCh are presented and discussed in terms of benefit to DevOps-environments., Comment: Post print of a paper presented at the 1st USDAI workshop and published in the SAFECOMP 2020 Workshop proceedings

It is becoming increasingly clear that an important task for wireless networks is to minimize the age of information (AoI), i.e., the timeliness of information delivery. While mainstream approaches generally rely on the real-time observation of user AoI and channel state, there has been little attention to solve the problem in a complete (or partial) absence of such knowledge. In this article, we present a novel study to address the optimal blind radio resource scheduling problem in orthogonal frequency division multiplexing access (OFDMA) systems towards minimizing long-term average AoI, which is proven to be the composition of time-domain-fair clustered round-robin and frequency-domain-fair intra-cluster sub-carrier assignment. Heuristic solutions that are near-optimal as shown by simulation results are also proposed to effectively improve the performance upon presence of various degrees of extra knowledge, e.g., channel state and AoI., Comment: Accepted on 05.06.2021 by the IEEE Transactions on Wireless Communications for publication

Network Slicing is expected to become a game changer in the upcoming 5G networks and beyond, enlarging the telecom business ecosystem through still-unexplored vertical industry profits. This implies that heterogeneous service level agreements (SLAs) must be guaranteed per slice given the multitude of predefined requirements. In this paper, we pioneer a novel radio slicing orchestration solution that simultaneously provides-latency and throughput guarantees in a multi-tenancy environment. Leveraging on a solid mathematical framework, we exploit the exploration-vs-exploitation paradigm by means of a multi-armed-bandit-based(MAB) orchestrator, LACO, that makes adaptive resource slicing decisions with no prior knowledge on the traffic demand or channel quality statistics. As opposed to traditional MAB methods that are blind to the underlying system, LACO relies on system structure information to expedite decisions. After a preliminary simulations campaign empirically proving the validness of our solution, we provide a robust implementation of LACO using off-the-shelf equipment to fully emulate realistic network conditions:near-optimal results within affordable computational time are measured when LACO is in place.

Intelligent connected vehicles equipped with wireless sensors, intelligent control system, and communication devices are expected to commercially launch and emerge on road in short-term. These smart vehicles are able to partially/fully drive themselves; collect data from sensors, make and execute decisions based on that data; communicate with other vehicles, pedestrians, and nodes installed on the road; and provide infotainment and value-added services, such as broadband transmission of ultra-high definition video, files/apps downloading and uploading, online gaming, access to social media, audio/video conference streaming (office-in-car), live TV streaming, etc.; and so on. In addition, it is also possible for autonomous vehicles to form a "platoon" on road; maintaining close proximity in order to reduce the consumption of fuel and/or emission of gas, decrease costs, increase safety, and enhance the efficiency of the legacy transportation system. These emerging vehicular applications demand a large amount of computing and communication capacity to excel in their compute-intensive and latency-sensitive tasks. Based on these facts, the authors of this paper presented a visionary concept -- "platoon-assisted vehicular cloud" -- that exploits underutilized resources in platoons to augment vehicular cloud aiming to provide cost-effective and on-demand computing resources. Moreover, the authors presented three potential scenarios and explained the exploitation of platoon resources and roadside infrastructure to facilitate new applications. Besides system design, the paper did also summarize a number of open research challenges with the purpose of motivating new advances and potential solutions to this field., Comment: This paper presented in European Symposium on Computer and Communications (ESCC 2019)

In recent years, the next generation of wireless communication (5G) plays a significant role in both industry and academy societies. Cellular Vehicle-to-Everything (C-V2X) communication technology has been one of the prominent services for 5G. For C-V2X transmission mode, there is a newly defined communication channel (sidelink) that can support direct C-V2X communication. Direct C-V2X communication is a technology that allows vehicles to communicate and share safety-related information with other traffic participates directly without going through the cellular network. The C-V2X data packet will be delivered to all traffic Users (UE) in the proximity of the Transmitter (Tx). Some UEs might not successfully receive the data packets during one transmission but the sidelink Tx is not able to check whether the Receivers (Rxs) get the information or not due to the lack of feedback channel. For enabling the strict requirements in terms of reliability and latency for C-V2X communication, we propose and evaluate one retransmission scheme and retransmission with different traffic speed scheme. These schemes try to improve the reliability of the safety-related data by one blind retransmission without requiring feedback. Although this retransmission scheme is essential to C-V2X communication, the scheme has a limitation in the performance aspect because of its redundant retransmission. Since radio resources for CV2X communication are limited, we have to detect the effect of retransmission on the performance of the communication system. To the end, the simulator for evaluating the proposed schemes for the C-V2X communication has been implemented, and the performances of the different communication schemes are shown through the Packet Reception Ratio (PRR)., Comment: 7 pages, 9 figures, VTC2020,fall

The emerging technology of multi-tenancy network slicing is considered as an essential feature of 5G cellular networks. It provides network slices as a new type of public cloud services, and therewith increases the service flexibility and enhances the network resource efficiency. Meanwhile, it raises new challenges of network resource management. A number of various methods have been proposed over the recent past years, in which machine learning and artificial intelligence techniques are widely deployed. In this article, we provide a survey to existing approaches of network slicing resource management, with a highlight on the roles played by machine learning in them., Comment: To appear in ZTE Communications, 2020

The combination of recent emerging technologies such as network function virtualization (NFV) and network programmability (SDN) gave birth to the novel Network Slicing paradigm. 5G networks consist of multi-tenant infrastructures capable of offering leased network "slices" to new customers (e.g., vertical industries) enabling a new telecom business model: Slice-as-a-Service (SlaaS). However, as the service demand gets increasingly dense, slice requests congestion may occur leading to undesired waiting periods. This may turn into impatient tenant behaviors that increase potential loss of the business attractiveness to customers. In this paper, we aim to i study the slicing admission control problem by means of a multi-queuing system for heterogeneous tenant requests, ii) derive its statistical behavior model, iii) find out the rational strategy of impatient tenants waiting in queue-based slice admission control systems, iv) prove mathematically and empirically the benefits of allowing infrastructure providers to share its information with the upcoming tenants, and v) provide a utility model for network slices admission optimization. Our results analyze the capability of the proposed SlaaS system to be approximately Markovian and evaluate its performance as compared to a baseline solution., Comment: Accepted by IEEE Transactions on Wireless Communications on 10.04.2020. arXiv admin note: substantial text overlap with arXiv:1901.06399, arXiv:1809.06815

The increasing demands for highly individual products as well as for flexible production lines represent new challenges. To address these demands, future plants must be highly flexible and dynamically reconfigurable. Current systems are usually based on wired technologies for the connection of sensors, actuators, and controlling or monitoring devices that allow only very limited dynamics. New applications, such as the use of robots, drones, or reconfigurable production lines, require the exploitation of wireless communication technologies. However, current technologies are not able to meet the high requirements in terms of latency, robustness, resilience and data rate. The introduction of the 5th generation (5G) cellular communication system will meet these requirements for the first time. Besides the use of radio-based solutions in new plants - so-called greenfield scenarios - deploying 5G also represents an efficient migration of existing plants - so-called brownfield scenarios - to Industry 4.0. In order to ensure that the challenging requirements are indeed meet in practical deployments of the new 5G technology, a tailor-made architecture is being developed within the Tactile Internet 4.0 (TACNET 4.0) project. As a basis for the design of the architecture, representative Industry 4.0 application scenarios, which are also be considered by the 3rd Generation Partnership Project (3GPP), were analyzed and compliance with the latest developments in the relevant standardization is also our target. The paper gives an overview of the considered use cases as well as the relevant reference architectures and the design process of the TACNET 4.0 architecture., Comment: Submitted to 24. ITG Fachtagung Mobilkommunikation

Platooning involves a set of vehicles moving in a cooperative fashion at equal inter-vehicular distances. Taking advantage of wireless communication technology, this paper aims to show the impact of network protocols on a platoon using a controller, based on the Cooperative Adaptive Cruise Control (CACC) principles. The network protocols used in this work are DSRC (Dedicated Short Range Communication) and LTE-V2V sidelink (Mode 4). The main focus of this work is to showcase the ability of the controller to maintain platoon stability despite having uncertainties in both, the platoon and the message delivery rates over the network protocols. The controller interacts with all vehicles using messages transmitted over the network protocols. The controller is designed to be responsible for micro-managing every vehicle in the platoon and to ensure that the platoon does not break under any circumstances. SUMO (Simulation of Urban MObility) is used as the simulation platform. Results indicate, that the controller manages to achieve platoon stability in all scenarios, unless a set number of consecutive messages are not transmitted, in which case it leads to collisions. This work also presents certain bottlenecks pertaining to wireless communication with vehicles.

In recent years, Cellular-Vehicle-to-Everything (CV2X) has been an emerging area of interest attracting both the industry and academy societies to develop, which is also a prominent emerging service for the next generation of the cellular network (5G). In the time of the development, standardization, and further improvement of 5G, so simulations are essential to test and optimize algorithms and procedures prior to their implementation process of the equipment manufactures. And CV2X communication is used for information exchange among the traffic participants with network-assisted which can reduce traffic accidents and improve traffic efficiency. Moreover, it is also the primary enabler for cooperative driving. But CV2X communication has to meet different Quality of Service (QoS) requirements (e.g., ultra-high reliability (99.999%) and ultra-low latency). Guaranteeing high-level reliability is a big challenge. In order to assess system performance, accurate simulations of simple setups, as well as simulations of more complex systems via abstracted models are necessary for the CV2X communication. For checking the performance of the C-V2X communication on a highway scenario, a system-level simulator has been implemented. And, this simulation has been carried out on the network (system-level) context. Finally, the analysis and the simulation results for the C-V2X communication are presented, which shows that different objectives can be met via system-level simulation., Comment: 5 pages, 5 figures, MKT'19 Osnabr\"uck, Germany