Integrating sensing, enabling network intelligence, and improving spectral efficiency are key drivers of the vision for sixth-generation (6G) wireless systems. Conventional pilot-based channel characterization methods incur significant radio-resource overhead, particularly in indoor traffic scenarios, whereas sensing-aided channel characterization offers a viable alternative. Digital twins (DTs) are seen as a promising enabler providing high-fidelity virtual representations of physical environments, which can enhance sensing-aided channel characterization. This paper proposes a DT framework for channel characterization in radio access networks (RANs), leveraging multimodal sensing. Ray tracing is performed on a fused and segmented multimodal point cloud that supports arbitrary placements of both transmitters and receivers, and the DT is validated using a bistatic radio link. In this work, we use received signal strength (RSS) and power delay profile (PDP) as the KPIs. Our results show that multimodal sensing significantly improves environmental awareness, achieving a relative mean absolute error of 2.5 % for RSS and below 15 % for PDP. Therefore, the DT facilitates accurate sensing-aided channel characterization in indoor environments, enabling closed-loop optimization in RAN.

In this paper, a collaborative 3D Digital Twin (C-3DDT) environment replicating a physical Fab Lab is proposed, validated, and evaluated over two sliced 5G systems: O-RAN and 3GPP. Extended Reality and C-3DDT technologies are expected to play a central role in future 6G services, enabling immersive and collaborative applications with demanding Quality of Service (QoS) requirements. To prepare for this vision, it is essential to evaluate 5G systems incorporating 6G-enabling features, such as network slicing and Artificial Intelligence (AI)-driven optimization. However, systematic assessments of 5G capabilities in such complex, interactive environments remain limited. The proposed, immersive C-3DDT platform supports remote collaboration and it is evaluated under sliced 5G configurations, including O-RAN and an AI-powered 3GPP-compliant RAN. AI-driven dynamic slice optimization is deployed to improve adaptability and resource efficiency of the system. Furthermore, the evaluations extend beyond traditional key performance indicators by incorporating a key value indicator analysis addressing cost and efficiency, sustainability, digital security, knowledge and learning, and quality of life. The results demonstrate the feasibility and effectiveness of C-3DDT environments over advanced 5G networks, offering insights for the transition toward secure, sustainable, and highly efficient 6G systems.

6G must be designed to withstand, adapt to, and evolve amid prolonged, complex disruptions. Mobile networks' shift from efficiency-first to sustainability-aware has motivated this white paper to assert that resilience is a primary design goal, alongside sustainability and efficiency, encompassing technology, architecture, and economics. We promote resilience by analysing dependencies between mobile networks and other critical systems, such as energy, transport, and emergency services, and illustrate how cascading failures spread through infrastructures. We formalise resilience using the 3R framework: reliability, robustness, resilience. Subsequently, we translate this into measurable capabilities: graceful degradation, situational awareness, rapid reconfiguration, and learning-driven improvement and recovery. Architecturally, we promote edge-native and locality-aware designs, open interfaces, and programmability to enable islanded operations, fallback modes, and multi-layer diversity (radio, compute, energy, timing). Key enablers include AI-native control loops with verifiable behaviour, zero-trust security rooted in hardware and supply-chain integrity, and networking techniques that prioritise critical traffic, time-sensitive flows, and inter-domain coordination. Resilience also has a techno-economic aspect: open platforms and high-quality complementors generate ecosystem externalities that enhance resilience while opening new markets. We identify nine business-model groups and several patterns aligned with the 3R objectives, and we outline governance and standardisation. This white paper serves as an initial step and catalyst for 6G resilience. It aims to inspire researchers, professionals, government officials, and the public, providing them with the essential components to understand and shape the development of 6G resilience.

This research compares and contrasts 5G and 6G networks in the context of communication systems for connected vehicles. Simulation-based tests were used to evaluate key performance metrics, including quality of service (QoS), throughput, latency, packet loss, signal strength, and handover success rate. The results show that 6G networks consistently outperform 5G across these areas, indicating substantial improvements in connected vehicle communications. These results highlight the transformative potential of 6G technology for future transportation systems, enabling faster, more reliable, and efficient communication between vehicles and infrastructure. This comparative analysis aims to inform the development of V2X communication technologies and support progress toward safer and more efficient transportation systems.

This paper presents a pioneering approach to developing remote Fabrication Laboratory (Fab Lab) using extended reality (XR) and 3D digital twins, enabled by cutting-edge advancements in private 5G networks. These XR Fab Labs enable multi-user remote collaboration and real-time control of R&D and manufacturing processes. Taking advantage of 3D digital twins and XR technologies, users can interact, review, and manipulate 3D models in a virtual space. The integration of ultra-reliable low-latency communication (URLLC) and network slicing within an Open Radio Access Network (O-RAN)-based private 5 G framework provides robust low-latency connectivity. An operational demonstration compared eMBB and URLLC slices under congestion, while a user Quality of Experience (QoE) survey revealed high usability and minimal perceived latency. This approach confirms the feasibility of integrating XR-based digital twins with 5 G slicing capability for remote design and manufacturing in cyber-physical spaces.

In an effort to improve road safety, the Finnish Meteorological Institute (FMI) worked on a project to develop a cutting-edge wireless traffic network connecting vehicles and infrastructure. The FMI team conducted extensive field measurments on Petajamaa and Sodankyla Airport test tracks by meticulously designing, refining, and piloting the measurements and related techniques. In this paper, our field measurements ranging from simple vehicle-to-vehicle (V2V) interactions to complex multi-hop scenarios involving multiple cars and roadside units using cellular based 5G networks are reported. The paper examines important metrics such as goodput time, latency, packet loss, and average throughput using state-of-the-art equipment such as Sunit vehicle PCs, laptops, modern smart phones, and antennas. Despite facing challenges such as GPS inaccuracies and varying vehicle speeds, this study provides valuable insights into the network's performance under different real-time conditions. The results have significant implications for understanding connectivity ranges and achievable data rates in real-world settings using 5G network. The findings from this paper have the potential to significantly impact road safety standards, offering a glimpse into the future of transportation and paving the way for safer roads worldwide.

Since the last decade, researchers have been continuously trying to implement and evaluate the performance of DAVN's (drone-assisted vehicular networks). DA VN efficiently integrates the networking and communication technologies of drones with connected vehicles (CV). In this paper, we demonstrate DA VN for road weather data exchange in drone-to-vehicle and drone-to-infrastructure scenarios. We use the real-time road weather and road traffic data that we obtained during our pilot measurements of these pilot scenarios in Northern Finland to carry out these pilot scenarios. Later, the designed and executed test scenarios are added to Wireshark and NS-3 (Network Simulator) to evaluate the performance of the 5G and ITS-G5 networks. The performance evaluation for DA VN was performed by considering the following parameters: end-to-end latency, packet drop ratio (PDR), and average throughput.

The basic idea of Heterogeneous Data for Enhanced Traffic Services (HDETS) is to facilitate different traffic services that utilize heterogeneous data to develop road safety services and improve resource utilization efficiency, i.e., electric energy and road weather services (RWS). The potential for smart traffic services is substantial, as the amount of heterogeneous data generated by real-time traffic environments to exploit situational awareness is much larger than the data generated today. In this paper, we discuss the unique aspects of HDETS by combining state-of-the-art cloud and edge architectures, novel 5G and 6G communication technologies, artificial intelligence (AI) methods, and deep knowledge from this application area. The first objective of HDETS is to analyze the data sources, which together enable recognizing emerging traffic situations and physical conditions affecting traffic. The second objective is to develop AI methods that are required for the service scenarios. The third objective is to develop a combined cloud and edge computing architecture for AI methods. The fourth objective is to study wireless communication technologies for this architecture, including 5G and 6G, short-range vehicle area networking (VANET), and visible light communication (VLC). Dealing with the above-mentioned objectives, this paper paves the way to respond to our research questions on data sources and AI methodology. It enables novel services, as well as cloud and edge architectures and communication technologies that fulfill the requirements set by these AI methods.

Since the last decade, researchers have been continuously trying to implement and evaluate the performance of Drone Assisted Vehicular Network (DAVN). A DAVN efficiently integrates the networking and communication technologies of drones with connected vehicles. DAVNs have a huge potential to offer a wide range of features for Intelligent Transport Systems (ITS) applications to improve traffic safety on roads. In this paper, we first discuss the architecture of a DAVN and outline its potential services for vehicular networks. Drones cooperate with infrastructure and vehicles to improve Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) network coverage, data collection capability, and efficiency of communication interworking. In this paper, we demonstrate the DAVN concept with regard to Drone-to-Vehicle (D2V) and Drone-to-Infrastructure (D2I) communications utilizing road meteorological data exchange. To perform these pilot scenarios, we use real-time weather and traffic data collected during our pilot measurements in Northern Finland. The executed and generated test scenarios are added to Wireshark and NS-2 (Network Simulators) to evaluate the performance of ITS-G5 and 5G Test Network (5GTN). The performance evaluation for DAVN is carried out by considering the following parameters: end-to-end delay, packet delivery ratio (PDR), packet loss and average throughput. Our results revealed that ITS-G5 performs better and more efficiently than 5G in D2V PDR scenarios, and 5G performs well in D2I PDR scenarios. Moreover, the 5G network presents better performance in the average throughput and D2I (in our case drone-to-RWS (Road-Weather-Station)) delay scenario in contrast to ITS-G5, and this is due to vehicles, haphazard nature of test track and the distance between the cars.

This Special Issue originates from the international conference 2021 Joint EuCNC & 6G Summit (Joint European Conference on Networks and Communications and 6G Summit), which was held in June 2021 in virtual format. The Technical Programme Chairs of the conference selected the best papers and invited authors to submit an extended version of their paper by at least one-third of their length. Only the top ranked papers were invited to this Special Issue, in order to fulfil its purpose. The main target was to collect and present quality research contributions in the most recent activities related to technologies, systems and networks beyond 5G. Through this Special Issue, the state-of-the-art is presented and the new challenges highlighted, regarding the latest advances on systems and network perspectives that are already being positioned beyond 5G, bridging as well with the evolution of 5G, including applications and trials. Therefore, the motivation for this Special Issue is to present the latest and finest results on the evolution of research of mobile and wireless communications, coming, but not exclusively (since Joint EuCNC & 6G Summit is a conference open to the whole research community), from projects co-financed by the European Commission within its R&D programmes.

This paper provides a tutorial on the most recent advances of event-driven metering (EDM) while indicating potential extensions to improve its performance. We have revisited the effects on signal reconstruction of (i) a fine-tuned procedure for defining power variation events, (ii) consecutive-measurements filtering that refers to the same event, (iii) spike filtering, and (iv) timeout parameter. We have illustrated via extensive numerical results that EDM can provide high-fidelity signal reconstruction while decreasing the overall number of acquired measurements to be transmitted. Its main advantage is to only store samples that are informative based on predetermined events, avoiding redundancy and decreasing the traffic offered to the underlying communication network. This tutorial highlights the key advantages of EDM and points out promising research directions.

Main research and development interest of 5G and beyond systems are focusing on solution for populated and hot spot areas, but public safety authorities need reliable communication solutions in rural and remote areas. Tactical bubbles—ad hoc‐type nonpublic communications networks built with the 3rd Generation Partnership Project‐based mobile technologies—offer mission critical communications services for public safety authorities in areas with bad mobile network coverage while also providing additional capacity in hot spot areas. In this experimental study, three interconnected bubbles acting on three different frequency bands—2.3 GHz (40), 2.6 GHz (7), and 3.5 GHz (n78)—are trialed. This article provides the analysis of different factors related to performance and user experience of tactical bubbles. Both ground‐level and aerial trial measurements, as well as simulations, were utilized to verify our configuration for the tactical bubbles and their fulfillment of the quality requirements. The performance and coverage of the tactical bubbles are evaluated in a trial, which represents authorities' search operations in a rural environment with hills, forests, and swamps. The achieved coverage range of the bubbles is more than 1000 m with the unmanned aerial system‐based measurements, whereas by car, the coverage is less than 600 m. The effect of obstacles (ie, buildings and hills) on the coverage area and performance of bubbles is significant, especially on car‐based measurements on the ground level.

The architectures of mobile networks have seen an unprecedented techno-economic transformation, fusing the telcommunications world within the cloud world, adding the spices of Software Engineering to the overall system design, and ultimately yielding the concept of Telco Cloud. This has brought significant benefits in terms of reducing expenditure and operational costs, flexibility in deployment, and a faster time to market. The key enablers are network function virtualization, software-defined networking, and edge/cloud computing. Artificial intelligence is also kicking in this arena. When all these technologies are well integrated, the creation and life-cycle management of fully programmable, flexible, service-tailored, and automated end-to-end network slices/services become possible. This will support diverse 5G and beyond 5G services, spanning from tactile IoT to pervasive robotics and immersive services. This paper introduces an unprecedented and disruptive vision for 6G that shifts the perception of future mobile networks from the old-fashioned concept of "network of networks" towards a new vision of "service of services." The paper then introduces the functional model of the envisioned system architecture, along with its components. It then provides a high-level description of the logical architecture.

Our society relies on connectivity and free movement of labor and knowledge. The current pandemic has proven us that we cannot always achieve this with the means we are accustomed to. Luckily ubiquitous technologies have achieved the level of maturity required to give us a solid grounding for creating accessible solutions for telexistence. Teleconferencing using mobile phones and even remote operable mobility platforms for those, is not a new approach. However, there are only few openly available and fabricable full solutions for this. In this study we present an architecture and solutions for a situation awareness digital twin with physical interactive teleconference infrastructure by fabricable platform and private 5G mobile network. The telepresence platform can be controlled via immersive Virtual Reality (VR) or a smartphone with an interface that has been integrated to a mirror-world like virtual environment. We present preliminary findings of a technical evaluation and in addition discuss future improvements for better accessibility and other use cases.

5G mobile communications have received enormous attention from the communication community, in particular for applications requiring low latency, as in Vehicle-to-vehicle (V2V) and Vehicle-to-infrastructure (V2I) communications in Intelligent Transport systems (ITS). 5G has already been studied through simulations and pilot use-cases in vehicular adhoc networks (VANETs) scenarios. Currently, the other prominent wireless technology is ITS-G5, a networking technology standardized by the European Telecommunications Standards Institute (ETSI) for vehicular communications. By integrating the ITS-G5 and 4G/5G networks, the advantages of both systems can be readily exploited by the V2I, V2V and V2X systems. In this article, we have investigated low-latency vehicular communications considering the combined operation of ITS-G5 and 5G networks. We specifically analyze the seamless handover process between ITS-G5 and 5G Test Network (5GTN) by conducting field measurements at the Finnish Meteorological Institute (FMI) test track in Northern Finland. We analyze the latency and packet drop during the seamless hand-off between the two wireless technologies. This article also discusses an advanced road weather services architecture that assures stable communication links for heterogeneous networking technologies. Results show that the heterogeneous network considerably improves the load balancing and communication link availability between VANETs and infrastructure.

While the fifth generation (5G) New Radio wireless system is being deployed across the globe, the wireless research community has started exploring what will the sixth generation (6G) be? 6G is expected to cater to societal and economic needs by integrating the biological, physical, and virtual worlds with the networks. The notion of multi-service communication introduced in 5G will be further diversified and expanded to include new service classes representing novel and emerging use cases that were not considered as a part of the 5G landscape. Ultra-reliable low-latency communications (URLLC) and their evolution in 6G are of particular interest given their prominent role in enabling future industrial Internet of Things (IIoT) applications. During 2020-2022, ETRI from South Korea and the University of Oulu from Finland convened a joint project to explore URLLC evolution towards the 6G era. This article summarizes the key highlights of the project and outlines its main findings. The project involved a study of future URLLC service classes and their potential enablers, along with a demonstration of remote monitoring of a smart factory over an intercontinental link. The project's proof-of-concept was able to demonstrate remote monitoring of ETRI's IIoT testbed from Finland at sub-300 ms service round trip time.

Existing ICT networks are characterized by high level of energy consumption. In order to power up 5G base station sites, rising energy cost and high carbon emissions are major concerns that need to be dealt with. To achieve carbon neutrality, ICT sector needs to transform base station sites in a self-sustainable manner using renewable energy sources, local batteries and energy conservation techniques, even in adverse weather conditions and unexpected power outages. In this paper, short term-forecasting models are studied for accurate energy consumption and production forecast. The proposed architecture provides adaptive energy conservation technique using time series data analysis and Long Short-Term Memory for 5GNR base station site which is independent of traditional power sources and is completely powered by green energy. The accuracy analysis of this study was performed by the Mean Square Error (MSE) and Root Mean Square Error (RMSE). The results show high accuracy levels of LSTM model in guiding short-term energy forecasting for green ICT networks.