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Alessandro Bazzi

Publications and source records attributed to Alessandro Bazzi.

At least 19 recordsLinked to original sources

The Role of Collective Perception and 5G NR-V2X Sidelink in Road Safety

Vehicles and roadside infrastructure are increasingly equipped with sensors capable of perceiving their surroundings. Sharing this information through vehicle-to-everything (V2X) communications is a key enabler of Day-2 applications and is supported by the ETSI collective perception service (CPS). While CPS is expected to play a fundamental role in future intelligent transportation systems, its operation may significantly increase channel load, posing challenges in terms of radio resource utilization, communication reliability, and information management. This paper reviews the current status of CPS standardization and investigates its impact in dense deployment scenarios where connected vehicles communicate through fifth-generation (5G) New Radio-V2X (NR-V2X) sidelink (SL) communications. The main contribution is a realistic evaluation of communication reliability, latency, channel occupancy, and information usefulness under different object-selection strategies for collective perception messages. The analysis is conducted through a network-level simulation framework integrating empirical object traces derived from real-world datasets, thereby avoiding the limitations of synthetic traffic models. Results show that perception message generation and radio access mechanisms are tightly coupled and should be jointly designed to maximize the benefits of collective perception services.

cs.NI

Decentralized Multi-Agent Urban Traffic Management via Spatio-Temporal Mobility Profile Planning

As modern cities face increasingly severe traffic congestion, connected and autonomous vehicles (CAVs) have emerged as a crucial enabling technology for next-generation intelligent traffic management. However, fully realizing this potential is hindered by the limitations of current paradigms. Existing approaches typically optimize localized interactions rather than system-wide efficiency, incur severe communication overhead, or lack the deterministic guarantees required for safe kinematic execution. Furthermore, current multi-agent adaptations are frequently restricted to small predefined scenarios, failing to scale across large and complex urban networks. To bridge this gap, this paper introduces VeloCity, a decentralized multi-agent spatio-temporal mobility profile planning framework designed for CAVs operating in arbitrary urban areas. To minimize vehicles' travel times, VeloCity distributes mobility profile optimization directly to individual CAVs. Vehicles query a localized traffic coordinator for a reservation table, independently compute their fastest conflict-free mobility profile, and reserve their requested space-time slots back with the coordinator. By natively adapting to any arbitrary road topology, the framework manages highly irregular urban areas without requiring scenario-specific tuning, all while guaranteeing collision-free and physically executable vehicle trajectories. Extensive simulations across four large-scale real-world urban maps (Tokyo, Manhattan, Rome, and Bologna) demonstrate the framework's scalability. Compared to established state-of-the-art models, VeloCity yields drastically lower travel times, tightly bounds delay variance, and successfully prevents congestion gridlocks even under extremely high vehicular densities.

cs.MA

Proactive URLLC Adaptation for Connected Vehicles Through ML-Based Channel Prediction

Connected and automated vehicles (CAVs) are expected to increasingly rely on 5G and future 6G ultra-reliable and low-latency communication (URLLC) services to support safety-critical and time-sensitive applications. Since wireless link conditions can vary rapidly in urban vehicular environments, proactively adapting service parameters based on future channel conditions is essential to maintain service continuity and reliability. In this paper, we investigate the use of machine learning (ML) techniques for channel quality prediction in vehicular URLLC scenarios. Specifically, we evaluate deep neural network (DNN) and long short-term memory (LSTM) models to forecast future channel conditions and enable proactive service adaptation with minimized performance degradation. The analysis is conducted using realistic simulations combining the SUMO traffic simulator and the Sionna-RT ray-tracing framework in a real urban environment reconstructed from OpenStreetMap data. Results show that ML-based prediction significantly outperforms approaches relying solely on past channel measurements and achieves performance close to the ideal case in which future channel conditions are perfectly known in advance. These findings demonstrate the potential of ML-driven prediction techniques to enhance the reliability and robustness of URLLC services for connected vehicular systems.

cs.NI

A Practical Implementation of Day-3 Cooperative Intersection with Automated Connected Mini-Cars

Cooperative driving enabled by connected and automated vehicles is expected to improve traffic efficiency and safety, particularly at intersections where traditional control mechanisms such as traffic lights introduce delays and unnecessary stops. Although cooperative intersection management algorithms have been widely studied, experimental demonstrations remain limited. This paper presents a real-time demonstration of cooperative intersection management using connected autonomous mini-cars. The testbed consists of multiple 1:10 scale vehicles equipped with autonomous driving capabilities and wireless communication modules that interact with a centralized controller responsible for scheduling their crossing of the intersection. Vehicles approaching the intersection exchange messages with the controller to set the appropriate mobility profile to traverse the intersection without stopping. The demonstration integrates autonomous driving, wireless communication, and cooperative control in a single experimental platform, providing a practical environment for validating cooperative intersection management concepts for future intelligent transportation systems.

cs.NI

5G NR-V2X Scheduling Approaches for CPM Variable Size Traffic

Collective perception messages (CPMs) introduce significant packet size variability due to dynamic object inclusion and periodic security overhead. While 5G NR-V2X Mode 2 typically employs semi-persistent scheduling (SPS) designed for periodic traffic with relatively stable packet sizes, the impact of realistic CPM-driven size fluctuations on distributed resource allocation remains insufficiently understood. This paper presents a comparative system-level evaluation of NR-V2X Mode 2 scheduling strategies under variable-size CPM traffic reconstructed from real-world perception datasets. We analyze dynamic scheduling and multiple SPS-based approaches, including padding-based allocation, aggressive size-driven reselection, and modulation and coding scheme (MCS) adaptation. Results show that packet size variability can significantly degrade reliability when scheduling stability is compromised. In particular, dynamic scheduling and aggressive reselection increase collision probability due to frequent resource reallocations. In contrast, SPS with padding converges to a stable resource allocation and provides robust performance, while MCS adaptation achieves the highest average packet reception ratio but with uneven reliability across packet types. The findings demonstrate that, under realistic CPM traffic, stability of resource usage is more critical than instantaneous load optimization, and provide design guidelines for CPS deployment over NR-V2X Mode 2.

cs.NI

Can NR-V2X Sidelink support A2A links?

In the context of 5G, 3GPP introduced New Radio vehicle to everything (NR-V2X) for direct vehicle-to-vehicle communication. However, starting from Release 18 the focus of the standard has been expanded from vehicles to any device and use case that can benefit from direct communication. In 3GPP terminology, the standard is now referred to simply as Sidelink communication. This standard allows direct communication between devices based on synchronous resource scheduling. Users can rely on controlled scheduling when in network coverage or, in the absence of coverage, autonomously select resources for transmission via a distributed resource allocation mechanism. Focusing on the autonomous resource allocation, this paper investigates the possibility of applying Release 18 Sidelink communication to Air-to-Air (A2A) links between airborne entities. The paper outlines the main challenges and required modifications to adapt the current standard for longer links in the order of kilometres. The analysis identifies the propagation delay as a critical limitation. Communications at distances over 42.4 km require a restriction of the user's transmitting opportunities. However, sidelink communication remains feasible for distances below this threshold without modifications to the standard.

cs.NI

Open-Source Based and ETSI Compliant Cooperative, Connected, and Automated Mini-Cars

The automotive sector is following a revolutionary path from vehicles controlled by humans to vehicles that will be fully automated, fully connected, and ultimately fully cooperative. Along this road, new cooperative algorithms and protocols will be designed and field tested, which represents a great challenge in terms of costs. In this context, in particular, moving from simulations to practical experiments requires huge investments that are not always affordable and may become a barrier in some cases. To solve this issue and provide the community with an intermediate step, we here propose the use of 1:10 scaled cooperative, autonomous, and connected mini-cars. The mini-car is equipped with a Jetson Orin board running the open Robot Operating System 2 (ROS2), sensors for autonomous operations, and a Raspberry Pi board for connectivity mounting the open source Open Stack for Car (OScar). A key aspect of the proposal is the use of OScar, which implements a full ETSI cooperative-intelligent transport systems (C-ITS) compliant stack. The feasibility and potential of the proposed platform is here demonstrated through the implementation of a case study where the Day-1 intersection collision warning (ICW) application is implemented and validated.

cs.RO

Analysis of Proactive Uncoordinated Techniques to Mitigate Interference in FMCW Automotive Radars

Modern vehicles increasingly rely on advanced driver-assistance systems (ADAS), with radars playing a key role due to their cost-effectiveness and reliable performance. However, the growing number of radars operating in the same spectrum raises concerns about mutual interference, which could lead to system malfunctions and potential safety risks. This study focuses on a scenario in which all vehicles are equipped with frequency-modulated continuous-wave (FMCW) radars, and it assesses the impact of interference on radar functionality - expressed in terms of probability of failure - by considering both direct and reflected signals. The radars may employ one of the following proactive mitigation methods to reduce the impact of interference, all of which require no inter-vehicle coordination but differ in complexity: (i) random carrier-frequency hopping on a frame-by-frame basis, (ii) random carrier-frequency hopping on a chirp-by-chirp basis, and (iii) a directional, compass-based method specifically addressing interference from opposite directions, which can be combined with either of the two previous methods. In this work, we assume realistic simulated road traffic scenarios and develop a novel model that captures correlated interference and accounts for the main radar setting parameters. Results reveal that dense scenarios pose a high risk of radar malfunctions. Among the analyzed methods, chirp-by-chirp frequency hopping emerges as the most effective approach to mitigate interference and ensure system reliability, but only when combined with a sufficiently large bandwidth. The compass-based method, on the other hand, shows limited effectiveness and appears not worth the additional system complexity.

cs.NI

V2N-Based Algorithm and Communication Protocol for Autonomous Non-Stop Intersections

Intersections are critical areas for road safety and traffic efficiency, accounting for a significant portion of vehicle crashes and fatalities. While connected and autonomous vehicle (CAV) technologies offer a promising solution for autonomous intersection management, many existing proposals either rely on computationally heavy centralized controllers or overlook the practical impairments of real-world communication networks. This paper introduces seamless mobility of vehicles over intersections (Moveover), a novel algorithm comprising a vehicle-to-network (V2N) communication protocol designed to let vehicles cross autonomous intersections without stopping. Moveover delegates trajectory and speed profile selection to individual vehicles, allowing each CAV to optimize them according to its unique kinematic characteristics. Simultaneously, a local intersection controller prevents collisions through deterministic conflict zone reservations. The algorithm is rigorously evaluated under both ideal and non-ideal networking conditions, specifically modeling 4G and 5G communication delays, across multiple layouts including single-lane, multi-lane, and roundabouts. Furthermore, we test Moveover on a real urban map with multiple intersections. Simulation results demonstrate that Moveover significantly outperforms baseline strategies, offering substantial improvements in travel times and reduced pollutant emissions.

cs.NI

Exploiting Repetitions and Interference Cancellation for the 6G-V2X Sidelink Autonomous Mode

In recent years, the Third Generation Partnership Project (3GPP) has developed the new radio-vehicle-to-everything (NR-V2X) sidelink standard, to enable direct communication between connected and autonomous vehicles (CAVs). Users can autonomously select radio resources for their transmissions with the Mode 2 channel access scheme, which can also operate under out-of-coverage conditions. However, Mode 2 performance is hindered by interference and packet collisions arising from dynamic mobile environments and limitations in assessing radio resource availability. The 3GPP specifications allow transmitting multiple copies of the same packet to improve reliability, though at the cost of increased channel congestion. This paper proposes to leverage receivers equipped with successive interference cancellation (SIC) capabilities, to exploit packet repetitions. Specifically, once a packet is successfully decoded the interfering contribution carried by repetitions can be cancelled from future or past received signals, enabling the decoding of new packets. Extensive highway scenario simulations demonstrate that the proposed solution significantly outperforms the legacy Mode 2 scheme, especially under high interference conditions, achieving improvements exceeding 100% in some cases.

cs.NI

Dual Orthogonal Projections for Multiuser Interference Cancellation in mmWave Beamforming With Uniform Planar Arrays

This paper investigates multiuser interference (MUI) cancellation for millimeter-wave (mmWave) beamforming in communication systems. We propose a linear algorithm, termed iterative dual orthogonal projections (DOP), which alternates between two orthogonal projections: one to eliminate MUI and the other to refine combiners, ensuring empirical convergence in spectral efficiency. Simulation results show that, with each iteration, the spectral efficiency of each user converges rapidly, closely approaching the theoretical optimum determined by dirty paper coding (DPC), surpassing existing linear benchmarks while maintaining low computational complexity. Furthermore, the proposed DOP algorithm is extended to support both fully-digital and hybrid beamforming architectures.

eess.SP

AREE-Based Decoupled Design of Hybrid Beamformers in mmWave XL-MIMO Systems

Hybrid beamforming has been widely employed in mmWave communications such as vehicular-to-everything (V2X) scenarios, as a compromise between hardware complexity and spectral efficiency. However, the inherent coupling between analog and digital precoders in hybrid array architecture significantly limits the computational and spectral efficiency of existing algorithms. To address this issue, we propose an alternating residual error elimination (AREE) algorithm, which decomposes the hybrid beamforming problem into two low-dimensional subproblems, each exhibiting a favorable matrix structure that enables effective decoupling of analog and digital precoders from the matrix product formulation. These subproblems iteratively eliminate each other's residual errors, driving the original problem toward the optimal hybrid beamforming performance. The proposed initialization ensures rapid convergence, while a low-complexity geometric channel SVD algorithm is developed by transforming the high-dimensional sparse channel into a low-dimensional equivalent, thereby simplifying the derivation of subproblems. Simulation results demonstrate that the AREE algorithm effectively decouples analog and digital precoders with low complexity, achieves fast convergence, and offers higher spectral efficiency than existing beamforming methods.

eess.SP

Multi-Channel Operation for the Release 2 of ETSI Cooperative Intelligent Transport Systems

Vehicles and road infrastructure are starting to be equipped with vehicle-to-everything (V2X) communication solutions to increase road safety and provide new services to drivers and passengers. In Europe, the deployment is based on a set of Release 1 standards developed by ETSI to support basic use cases for cooperative intelligent transport systems (C-ITS). For them, the capacity of a single 10 MHz channel in the ITS band at 5.9 GHz is considered sufficient. At the same time, the ITS stakeholders are working towards several advanced use cases, which imply a significant increment of data traffic and the need for multiple channels. To address this issue, ETSI has recently standardized a new multi-channel operation (MCO) concept for flexible, efficient, and future-proof use of multiple channels. This new concept is defined in a set of new specifications that represent the foundation for the future releases of C-ITS standards. The present paper provides a comprehensive review of the new set of specifications, describing the main entities extending the C-ITS architecture at the different layers of the protocol stack, In addition, the paper provides representative examples that describe how these MCO standards will be used in the future and discusses some of the main open issues arising. The review and analysis of this paper facilitate the understanding and motivation of the new set of Release 2 ETSI specifications for MCO and the identification of new research opportunities.

cs.NI

A Methodology for Abstracting the Physical Layer of Direct V2X Communications Technologies

Recent advancements in V2X communications have greatly increased the flexibility of the physical and medium access control (MAC) layers. This increases the complexity when investigating the system from a network perspective to evaluate the performance of the supported applications. Such flexibility needs in fact to be taken into account through a cross-layer approach, which might lead to challenging evaluation processes. As an accurate simulation of the signals appears unfeasible, a typical solution is to rely on simple models for incorporating the physical layer of the supported technologies, based on off-line measurements or accurate link-level simulations. Such data is however limited to a subset of possible configurations and extending them to others is costly when not even impossible. The goal of this paper is to develop a new approach for modelling the physical layer of vehicle-to-everything (V2X) communications that can be extended to a wide range of configurations without leading to extensive measurement or simulation campaign at the link layer. In particular, given a scenario and starting from results in terms of packet error rate (PER) vs. signal-to-interference-plus-noise ratio (SINR) related to a subset of possible configurations, we derive one parameter, called implementation loss, that is then used to evaluate the network performance under any configuration in the same scenario. The proposed methodology, leading to a good trade-off among complexity, generality, and accuracy of the performance evaluation process, has been validated through extensive simulations with both IEEE 802.11p and LTE-V2X sidelink technologies in various scenarios.

cs.NI

Adaptive Repetitions Strategies in IEEE 802.11bd

A new backward compatible WiFi amendment is under development by the IEEE bd Task Group towards the so-called IEEE 802.11bd, which includes the possibility to transmit up to three repetitions of the same packet. This feature increases time diversity and enables the use of maximum ratio combining (MRC) at the receiver to improve the probability of correct decoding. In this work, we first investigate the packet repetition feature and analyze how it looses its efficacy increasing the traffic as an higher number of transmissions may augment the channel load and collision probability. Then, we propose two strategies for adaptively selecting the number of transmissions leveraging on an adapted version of the channel busy ratio (CBR), which is measured at the transmitter and is an indicator of the channel load. The proposed strategies are validated through network-level simulations that account for both the acquisition and decoding processes. Results show that the proposed strategies ensure that devices use optimal settings under variable traffic conditions.

cs.NI

Performance Analysis of IEEE 802.11p Preamble Insertion in C-V2X Sidelink Signals for Co-Channel Coexistence

Spectrum scarcity is one of the main challenges of future wireless technologies. When looking at vehicle-to-everything (V2X), this is amplified as spectrum sharing could impact road safety and traffic efficiency. It is therefore of particular importance to study solutions that allow the coexistence, in the same geographical area and in the same channels, of what are today the main V2X access technologies, namely IEEE 802.11p and sidelink LTE-V2X Mode 4. In this work, in addition to investigating the impact of the reciprocal interference, which we demonstrate to have a strong impact especially on the first and in congested channel conditions, a mitigation solution is extensively studied, which is based on the insertion of the IEEE 802.11p preamble at the beginning of the LTE-V2X sidelink transmission. The proposal, which is also under discussion within the standardization bodies, requires no modifications to the IEEE 802.11p protocol stack and minor changes to LTE-V2X sidelink. This solution is directly applicable to upcoming IEEE 802.11bd and extendable to NR-V2X sidelink. The paper shows, through analysis and simulations in free-flow and dense scenarios, that the proposal allows for a mitigation of collisions caused by co-channel coexistence under low to high-load channel conditions and that the improvement is also granted in congested cases when combined with additional countermeasures. Regarding the latter aspect, in particular, different approaches are compared, demonstrating that acting on the congestion control mechanisms is a simple but effective solution.

cs.NI

Optimizations for Hardware-in-the-Loop-Based V2X Validation Platforms

Connectivity and automation are increasingly getting importance in the automotive industry, which is observing a radical change from vehicles driven by humans to fully automated and remotely controlled ones. The test and validation of all the related devices and applications is thus becoming a crucial aspect; this is raising the interest on hardware-in-the-loop (HiL) platforms which reduce the need for complicated field trials, thus limiting the costs and delay added to the process. With reference to the test and validation of vehicle-to-everything (V2X) communications aspects, and assuming either sidelink LTE/5GV2X or IEEE 802.11p/bd technologies, in this work we focus on the real-time HiL simulation of the information exchanged by one vehicle under test and the surrounding, simulated, objects. Such exchange must be reproduced in a time-efficient manner, with elaborations done fast enough to allow testing the applications in real-time. More precisely, we discuss the simulation of nonideal positioning and channel propagation taking into account current impairments. We also provide details on optimization solutions that allowed us to trade-off minor loss in accuracy with a significant reduction of the computation time burden, reaching up to more than one order of magnitude speed increase in our experiments.

cs.NI

Co-channel Coexistence: Let ITS-G5 and Sidelink C-V2X Make Peace

In the last few years, two technologies have been developed to enable direct exchange of information between vehicles. These technologies, currently seen as alternatives, are ITS-G5, as commonly referred in Europe, and sidelink LTE-vehicle-to-everything (LTE-V2X) (one of the solutions of the so-called cellular-V2X, C-V2X). For this reason, the attention has been mostly concentrated on comparing them and remarking their strengths and weaknesses to motivate a choice. Differently, in this work we focus on a scenario where both are used in the same area and using the same frequency channels, without the assistance from any infrastructure. Our results show that under co-channel coexistence the range of ITS-G5 is severely degraded, while impact on LTE-V2X is marginal. Additionally, a mitigation method where the CAM data generation is constrained to periodical intervals is shown to reduce the impact of co-channel coexistence, with less degradation on ITS-G5 performance and even improvement for LTE-V2X.

cs.NI