Eugenio Moro

This paper presents VaN3Twin—the first open source, full-stack Network Digital Twin (NDT) framework for simulating the coexistence of multiple Vehicle-to-Everything (V2X) communication technologies with accurate physical-layer modeling via ray tracing. VaN3Twin extends the ms-van3t simulator by integrating Sionna Ray Tracer (RT) in the loop, enabling high-fidelity representation of wireless propagation, including diverse Line of Sight (LoS) conditions with a focus on LoS blockage due to other vehicles’ meshes, Doppler effect, and site-dependent effects—e.g., scattering and diffraction. Unlike conventional simulation tools, the proposed framework supports realistic coexistence analysis across Dedicated Short Range Communication (DSRC) and Cellular-V2X (C-V2X) technologies operating over a shared spectrum. A dedicated interference tracking module captures cross-technology interference at the time-frequency resource block level and enhances Signal to Interference plus Noise Ratio (SINR) estimation by eliminating artifacts such as the bimodal behavior induced by separate LoS/NLoS propagation models. Compared to field measurements, VaN3Twin reduces application-layer disagreement by 50% in rural and over 70% in urban environments with respect to current state of the art simulation tools, demonstrating its value for scalable and accurate digital twin–based V2X coexistence simulation.

Smart Radio Environment (SRE) is a central paradigm in 6 G and beyond, where integrating Smart Radio Environment (SRE) components into the network planning process enables optimized performance for high-frequency Radio Access Network (RAN). This paper presents a comprehensive planning framework utilizing realistic urban scenarios and channel models to analyze diverse SRE components, including Reconfigurable Intelligent Surface (RIS), Network-Controlled Repeater (NCR), and advanced technologies like Simultaneous Transmitting and Reflecting RIS (STAR-RIS) and Trisectoral NCR (3SNCR). We propose two optimization strategies—Full Coverage Minimum Cost (FCMC) and Maximum Budget-Constrained Coverage (MBCC)—that address key cost and coverage objectives by considering both physical characteristics and scalable costs of each component, influenced by factors such as NCR amplification gain and RIS dimensions. Extensive numerical results demonstrate the significant impact of these models in enhancing network planning efficiency for high-density urban environments.

The increasing demand for mobile bandwidth is driving 5G networks toward the use of high-frequency spectrum, particularly the upper-6 GHz and mmWave bands. While these bands offer vast bandwidth potential, their propagation characteristics raise critical deployment challenges. This paper presents the first direct, on-field comparative evaluation of 5G standalone (SA) macro-cell deployments operating in these two bands, conducted in Milan, Italy. We show that the upper-6 GHz band can deliver wide-area urban coverage (up to 600 meters) with stable gigabit-level downlink throughput, even in Non-Line of Sight (NLoS) scenarios. mmWave, traditionally deemed unsuitable for NLoS, exhibits strong performance via urban reflections, achieving up to 1.3 Gbps in downlink and 250 Mbps in uplink. Furthermore, outdoor-to-indoor connectivity at mmWave frequencies proves viable through glass facades, challenging pessimistic assumptions about penetration losses. These findings, derived from synchronized deployments and extensive measurements, provide new insights into the complementary roles of these bands and the practical feasibility of their integration into future 5G networks.

Vehicular communications integrated with the radio access network (RAN) are envisioned as a breakthrough application for the evolution of cellular networks, including both current fifth generation (5G) and future sixth generation (6G) systems. However, traditional RANs face challenges in achieving the flexibility required to optimize sophisticated control mechanisms and enhance performance metrics, such as latency and reliability, to meet the diverse and demanding requirements of the vehicle-to-everything (V2X) environment. In contrast, the features of Open RAN (O-RAN) support advanced use cases, as its core paradigms provide an ideal framework for orchestrating vehicular communication. Although the high potential stemming from their integration can be easily seen and recognized, the effective combination of the two ecosystems is an open issue. Conceptual and architectural advances are mandatory for O-RAN to be capable of facilitating network intelligence in V2X. In this work, we introduce mobi-O-RAN, a technological proposition pioneering the integration of the two strategies for seamlessly incorporating V2X control within O-RAN’s ecosystem. First, mobi-O-RAN’s architecture is proposed and discussed. Then, a set of key V2X challenges is identified, and mobi-O-RAN-based solutions are proposed, paired with extensive numerical analysis to support their effectiveness. While our study primarily focuses on 5G NR V2X, we also highlight how mobi-O-RAN can serve as a foundation for future 6G vehicular networks, leveraging its programmability and network intelligence capabilities. Results prove the improved performance of mobi-O-RAN in terms of raw throughput, network resilience, and control overhead. Our results validate the proposed enabling architecture and confirm the potential of mobi-O-RAN in support of V2X communications.

Direct communication among vehicles, namely vehicle-to-vehicle (V2V), as part of vehicle-to-everything (V2X) system, will enable most of the upcoming Connected and Autonomous Vehicles (CAVs) applications. Nevertheless, the challenging requirements imposed by the vehicular environment necessitate advanced control mechanisms. Traditional Radio Access Networks (RANs) lack the necessary flexibility to address these control needs. The emerging Open RAN (O-RAN) concept offers a promising solution for orchestrating the V2X network. However, the seamless integration of these ecosystems remains an unresolved challenge. This article promotes a novel integration architecture that ensures the V2X control within O-RAN. We propose a novel architecture that establishes a low frequencies O-RAN-based control plane to ensure reliable and efficient multihops connectivity among CAVs at millimeter wave (mmWave). To examine and test the technological feasibility of this integrated architecture, we extend current Network Simulator 3 (ns-3) modules, leading to a simulation framework for experimenting with O-RAN-empowered V2X system. Such an integrated framework is used to show the benefits in a specific V2V challenge: link and relays selection. This case study serves as a practical example of a new O-RAN solution that effectively addresses the challenges of V2X communications. Numerical results showcase the improved reliability up to 60 to distributed and unmanaged solutions, supporting the viability of the proposed architecture

In a world where positioning is becoming increasingly important and emerging applications have progressively tighter requirements, the current satellite-based positioning solutions can not address their needs. We propose a new network-based positioning approach based on O-RAN 5G. The solution is easily deployable, transparent to the users, and flexible to the application needs, thanks to the programmability of the network. This is the first step towards a positioning network service targeting a flexible accuracy level, minimizing the number of parameters, and optimizing the resource and computation utilization.

In the never-ending pursuit of bandwidth, mid-bands have been recently reconsidered as the primary spectrum for 5G NR and its evolution. Laying between the crowded lower frequency bands and the propagation-unfriendly higher bands (i.e., millimeter wave), the upper 6 GHz band (6425-7125 MHz) presents a valuable compromise between capacity and coverage. Recognizing its potential, the research community has expressed interest in this spectrum and conducted several studies. Despite this enthusiasm, the deployment of upper 6 GHz testbeds remains elusive. This paper aims to address this gap by presenting the results of a comprehensive measurement campaign conducted on a 5G NR cellular system operating in the upper 6 GHz band (6425-7125 MHz), specifically deployed within the Politecnico di Milano campus. Our objective was to evaluate the system's performance in a realistic environment and provide insights supported by empirical measurements. The measurement campaign yielded positive results, showcasing a remarkable channel capacity in urban areas, which remained consistently high even at the cell edge and in challenging non-line-of-sight and outdoor-to-indoor scenarios.

Edge computing has been recently introduced to bring computational capabilities closer to end-users of modern network-based services, supporting existing and future delay-sensitive applications by effectively addressing the high propagation delay issue that affects cloud computing. However, the problem of efficiently and fairly managing the system resources presents particular challenges due to the limited capacity of both edge nodes and wireless access networks and the heterogeneity of resources and services’ requirements. To this end, we propose a techno-economic market where service providers act as buyers, securing both radio and computing resources to execute their associated end-users’ jobs while being constrained by a budget limit. We design an allocation mechanism that employs convex programming to find the unique market equilibrium point that maximizes fairness while ensuring that all buyers receive their preferred resource bundle. Additionally, we derive theoretical properties that confirm how the market equilibrium approach strikes a balance between fairness and efficiency. We also propose alternative allocation mechanisms and give a comparison with the market-based mechanism. Finally, we conduct simulations to numerically analyze and compare the performance of the mechanisms and confirm the market model's theoretical properties.

Edge computing has been recently introduced as a way to bring computational capabilities closer to end users of modern network-based services, in order to support existent and future delay-sensitive applications by effectively addressing the high propagation delay issue that affects cloud computing. However, the problem of efficiently and fairly manage the system resources presents particular challenges due to the limited capacity of both edge nodes and wireless access networks, as well as the heterogeneity of resources and services' requirements. To this end, we propose a techno-economic market where service providers act as buyers, securing both radio and computing resources for the execution of their associated end users' jobs, while being constrained by a budget limit. We design an allocation mechanism that employs convex programming in order to find the unique market equilibrium point that maximizes fairness, while making sure that all buyers receive their preferred resource bundle. Additionally, we derive theoretical properties that confirm how the market equilibrium approach strikes a balance between fairness and efficiency. We also propose alternative allocation mechanisms and give a comparison with the market-based mechanism. Finally, we conduct simulations in order to numerically analyze and compare the performance of the mechanisms and confirm the theoretical properties of the market model.