Most applications and services of Cooperative Intelligent Transport Systems (C-ITS) rely on accurate and continuous vehicle location information. The traditional localization method based on the Global Navigation Satellite System (GNSS) is the most commonly used. However, it does not provide reliable, continuous, and accurate positioning in all scenarios, such as tunnels. Therefore, in this work, we present an algorithm that exploits the existing Vehicle-to-Infrastructure (V2I) communication channel that operates within the LTE-V frequency band to acquire in-tunnel vehicle location information. We propose a novel solution for vehicle localization based on Doppler shift and Time of Arrival measurements. Measurements performed in the Beveren tunnel in Antwerp, Belgium, are used to obtain results. A comparison between estimated positions using Extended Kalman Filter (EKF) on Doppler shift measurements and individual Kalman Filter (KF) on Doppler shift and Time of Arrival measurements is carried out to analyze the filtering methods performance. Findings show that the EKF performs better than KF, reducing the average estimation error by 10 m, while the algorithm accuracy depends on the relevant RF channel propagation conditions and other in-tunnel-related environment knowledge included in the estimation. The proposed solution can be used for monitoring the position and speed of vehicles driving in tunnel environments.

This paper analyses the experimentally-assessed dual-polarized (DP) mobile channel in a tunnel environment under traffic conditions. We investigate the impact of antenna polarization and radiation pattern on the non-stationary vehicle-to-infrastructure (V2I) channel. Basic channel evaluation metrics are examined including path gain, co-polarization ratio (CPR), and cross-polarization discrimination (XPD). In addition, the stationarity region is estimated using the channel correlation function approach, and used to calculate the time-varying delay and Doppler power profiles. Statistical models are presented for parameters like CPR, XPD, RMS delay and Doppler spreads, where the lognormal distribution provides the best fit. The polarization and the opening angle of the antennas into the propagation channel are found to strongly influence the observed non-stationarity of the channel. They impact the degree of multipath richness that is captured, thus providing different path gain, delay and Doppler spreads. Based on our analysis, the directional antenna with vertical polarization provides the longest stationarity time of 400 ms at 90 km/h, as well as the lowest path loss and dispersion. Furthermore, the DP channel capacity is calculated and its dependence on different normalization approaches is investigated. We propose a more accurate normalization for the DP channels that takes the conservation of energy into account. Moreover, the subchannels correlation coefficients are determined. While the condition number is found to be low on average, the correlation results show high correlation among the DP subchannels. As conclusion, we show how the CPR and XPD play the main role in providing multiplexing gain for DP tunnel channels.

Integrated sensing and communication (ISAC) enables radio systems to simultaneously sense and communicate with their environment. This paper, developed within the Hexa-X-II project funded by the European Union, presents a comprehensive cross-layer vision for ISAC in 6G networks, integrating insights from physical-layer design, hardware architectures, AI-driven intelligence, and protocol-level innovations. We begin by revisiting the foundational principles of ISAC, highlighting synergies and trade-offs between sensing and communication across different integration levels. Enabling technologies (such as multiband operation, massive and distributed MIMO, non-terrestrial networks, reconfigurable intelligent surfaces, and machine learning) are analyzed in conjunction with hardware considerations including waveform design, synchronization, and full-duplex operation. To bridge implementation and system-level evaluation, we introduce a quantitative cross-layer framework linking design parameters to key performance and value indicators. By synthesizing perspectives from both academia and industry, this paper outlines how deeply integrated ISAC can transform 6G into a programmable and context-aware platform supporting applications from reliable wireless access to autonomous mobility and digital twinning.

Sub-THz communications are envisioned to unlock ultra-high data rates, ultra-low latencies, and massive connectivity in future wireless systems by utilizing bandwidths of up to tens of GHz. This paper presents the holistic perspective on sub-THz communications developed within the European sixth-generation (6G) flagship project Hexa-X-II. According to this perspective, successfully deploying sub-THz systems will require addressing several physical-layer (PHY) challenges associated with the harsh signal propagation and hardware limitations. In addition, sub-THz systems will drive advancements in essential wireless applications beyond communications, such as joint communications and sensing (JCAS). In this context, we present a collection of technical contributions and key findings from the Hexa-X-II project that have shaped this perspective. In contrast to existing works, these efforts collectively tackle the fundamental PHY challenges of sub-THz communications, i.e., understanding and modeling of radio propagation, radio-frequency (RF) power consumption and complexity, and hardware impairments. To achieve this, we present several results across three core areas, i.e., signal propagation and channel modeling, RF transceiver design, and PHY enablers, offering useful insights into the development of sub-THz systems. Lastly, we provide an overview of sub-THz JCAS, emphasizing it as one of the most promising applications in the sub-THz range.

The future of transportation systems is going towards autonomous and assisted driving, aiming to reach full automation. There is huge focus on communication technologies expected to offer vehicular application services, of which most are location-based services. This paper provides a study on localization accuracy limits using vehicle-to-infrastructure communication channels provided by IEEE 802.11p and LTE-V, considering two different vehicular network designs. Real data measurements obtained on our highway testbed are used to model and simulate propagation channels, the position of base stations, and the route followed by the vehicle. Cramer–Rao lower bound, geometric dilution of precision, and least square error for time difference of arrival localization technique are investigated. Based on our analyses and findings, LTE-V outperforms IEEE 802.11p. However, it is apparent that providing larger signal bandwidth dedicated to localization, with network sites positioned at both sides of the highway, and considering the geometry between vehicle and network sites, improve vehicle localization accuracy.

In the public safety sector, 5G offers immense opportunities for enhancing mission-critical services by provisioning virtualized service functions at the network edge, which enables achieving high reliability and low-latency. One of these mission-critical services is Back Situation Awareness (BSA) that supports Emergency Vehicles (EmVs) by increasing awareness about them on the roads. In this paper, we introduce an on-demand BSA application service, which has been developed for multi-domain Multi-Access Edge Computing (MEC) systems, enabling early notification for vehicles on the Estimated Time of Arrival (ETA) of an approaching EmV. The state-of-the-art approaches inform civilian vehicles about EmVs only when they are in a close proximity (up to 300m). However, in some situations (e.g., in congested areas), this may not be enough for the civilian vehicles to safely and timely maneuver out of the lane of an EmV. Our approach is, to the best of our knowledge, a unique way to significantly extend this awareness by creating an orchestrated 5G-based MEC deployment of BSA application service on optimally selected edges, thereby stretching over multiple edge domains and even countries. While consuming the real-time location, speed, and heading of an EmV, such application service affords the drivers with sufficient time to create a clear corridor, allowing the EmV to pass through unhindered in a safe manner thereby increasing the mission success. The detailed design and the performance analysis of the BSA application service that has been created following modern cloud-native principles based on Docker and Kubernetes, is presented in terms of the impact of emergency scale on the MEC system resources and service response time. Moreover, we also introduce a metric called panic indicator, which depicts how the proposed BSA service can potentially help in enabling drivers to calmly maneuver out of the path of an EmV, thereby increasing road safety.