Connected and automated driving V2X (Vehicle-to-Everything) services generate aperiodic traffic of variable size that can produce packet collisions in sidelink Cellular V2X or C-V2X communications when vehicles autonomously select their radio resources. A significant portion of these collisions stem from unutilized reservations that occur when a vehicle does not have a packet to be transmitted in a resource it had previously reserved. Unutilized reservations increase transmissions on selected resources (not-reserved), and augment the risk of packet collisions as vehicles cannot reserve resources for their following transmission. This paper addresses this challenge for the first time by introducing V2X Rebroadcasting , a novel and standard-compliant scheme that enables vehicles to rebroadcast packets from other vehicles in detected unutilized reservations. Unlike existing state-of-the-art mechanisms, the proposed scheme can be applied to improve the effectiveness of C-V2X communications for any V2X message and traffic patterns. V2X Rebroadcasting provides two main benefits. First, the vehicle can use the rebroadcasted packets to reserve resources for its next transmission, preventing other vehicles from selecting those resources and reducing packet-collision risk. Second, the proposal improves the reliability of the rebroadcasted packets, as the additional transmission may help overcome propagation losses or collisions experienced by the original packet. We evaluate V2X Rebroadcasting over 5G NR V2X mode 2 under realistic reference scenarios with different vehicle densities and traffic loads. The results indicate that the proposal can yield a more than 2x reduction in the probability of packet collisions and improves the reliability of V2X communications compared to the standard 5G NR V2X mode 2, even under challenging channel-load conditions. In these scenarios, V2X Rebroadcasting can improve the Packet Delivery Ratio (PDR) by up to 20% at short to medium distances, where safety-critical V2X data is particularly relevant, and it can also more than double the range at which high PDR levels are maintained.

Future 6 G networks are envisioned as a “network of networks” (NoN) ecosystem, integrating communication and computing resources across multiple domains. At the deep edge, IoT and end-user devices will form subnetworks for local communication and distributed task processing. These subnetworks will seamlessly integrate into the NoN ecosystem, creating an IoT-edge-cloud continuum. The unified resources across this continuum facilitate dynamic and scalable task offloading, unlocking new possibilities to support emerging services, including critical vertical services with stringent reliability and deterministic service level requirements. In this context, this paper demonstrates that a deterministic approach to task offloading and resource (communication and computing) allocation in the IoT-edge-cloud continuum not only ensures deterministic service levels but also enhances scalability compared to existing task offloading and resource allocation methods. By flexibly managing task completion deadlines while maintaining deterministic (i.e. bounded latency) service levels, deterministic policies achieve a more balanced workload and resource distribution across the continuum, ultimately improving scalability.

Next generation wireless networks must sustain deterministic service levels to support emerging time-sensitive applications. The ability to guarantee bounded latencies depends on the efficient management of radio resources. Several studies propose leveraging the native intelligence of future networks to develop predictive schedulers capable of efficiently managing resources. However, existing proposals focus on semistatic scheduling, where resources are reserved based on traffic predictions, and these reservations are susceptible to inefficiencies due to prediction inaccuracies. This study advances the state of the art with a novel predictive dynamic scheduling scheme that avoids such inefficiencies, and leverages traffic predictions to allocate resources to incoming requests that meet their latency requirements while avoiding resources likely to be needed by future predicted packets. Our results demonstrate that the proposed predictive dynamic scheduling effectively supports deterministic communications in scenarios with mixed traffic flows and varying QoS requirements.

Future cellular networks will sustainably integrate computing, intelligence and services within a “network of networks” ecosystem that includes IoT devices and subnetworks for local communications and distributed processing. This integration creates an IoT-edge-cloud continuum that enables opportunistic task offloading across the continuum, enhancing network performance, reducing response times and allowing a flexible resource allocation that can facilitate the system to scale according to demand. Future networks should also natively support deterministic service levels for critical and time-sensitive vertical applications. In this paper, we propose a deterministic task offloading and resource allocation scheme for the joint management of communication and computing resources in the IoT-edge-cloud continuum. The proposed scheme prioritizes task completion before deadlines over minimizing the latency in the execution of individual tasks. The scheme leverages flexible latencies across tasks to support a higher number of tasks through a more efficient management of computing and communication resources that better adapts to scenarios with constrained resources.

Future wireless networks must enhance their capacity to sustain deterministic service levels and support emerging time-sensitive services in key verticals. The ability to guarantee bounded latencies heavily depends on efficient radio resource management. Configured Grant (CG) scheduling can reduce latency by pre-allocating resources, but its effectiveness and efficiency decrease under variable traffic patterns. This study presents a novel predictive CG scheduling scheme that pre-allocates resources based on traffic predictions while accounting for prediction inaccuracies. By considering these inaccuracies, the scheme significantly improves the ability to meet bounded latency requirements, which are essential for supporting deterministic service levels. Our evaluations show that the proposed scheme significantly enhances the capacity to support deterministic service levels while improving resource utilization, even in scenarios with variable and mixed traffic flows with diverse requirements.

In this paper, we demonstrate how the network latency, the longitudinal velocity and the path curvature affect performance of the teleoperated driving (ToD). The performance of a ToD system is studied analytically through stability analysis of a dimensionless vehicle dynamics model with a scaled delay, which integrates the end-to-end (E2E) latency and the longitudinal velocity of the vehicle. We also establish a numerical simulation framework for ToD while incorporating a stochastic latency in the control loop arising from vehicle-to-network-to-vehicle (V2N2V) communication through a wireless network. The stochasticity of the latency mostly comes from the network scalability challenges to support high video bitrates, which also leads to packet drops. We provide simulation results of teleoperating a vehicle in a realistic parking lot scenario and demonstrate the effects of speed, curvature and stochastic latency on the maneuver performance.

Teleoperated driving (ToD) enables the remote driving or control of vehicles. For this purpose, vehicles must transmit video feeds to the ToD control center so that the remote operator is fully aware of the driving conditions and can safely control the vehicle. 5G (and beyond) networks are fundamental for the deployment of ToD as they can provide the low latency, reliable and broadband connection necessary to connect the vehicle and ToD control center. However, it is unclear whether common 5G network architectures and configurations are well-suited to support the simultaneous teleoperation of multiple vehicles with demanding uplink bandwidth, as current networks are mainly configured to support mobile broadband services. This paper demonstrates that MEC or edge-based 5G networks are better suited to support and scale the ToD service than centralized networks, and quantifies the bandwidth required to simultaneously teleoperate multiple vehicles under various 5G network architectures and configurations, including different duplexing modes and TDD frame structures. Finally, the study shows that the configuration of the control channels can help mitigate the impact that the processing time of the video feeds has on the capacity to support and scale the ToD service.

The 5G New Radio (NR) Vehicle-to-Everything (V2X) Sidelink (SL) standard defines multiple DeModulation Reference Signal (DMRS) patterns to support direct vehicular communications in high mobility scenarios. The DMRS pattern is a pre-defined sequence of signals that can be adapted for the transmission of each Transport Block (TB), and is used to estimate the channel response and mitigate the impact of the Doppler shifts experienced by the received signal in high relative speed conditions. The standard defines multiple DMRS patterns, but it does not provide any recommendations to indicate when each pattern should be used. To this end, this study presents an exhaustive analysis of the impact that the DMRS patterns have on the link level performance of NR V2X SL communications, deriving the first set of NR V2X SL recommendations on the DMRS pattern selection. The recommendations identify the maximum Modulation and Coding Scheme (MCS) that can be supported by each DMRS pattern to ensure high reliability levels, and cover different relative speeds, propagation scenarios, and number of subchannels. We also openly release the link level results generated and analysed in this study to derive the recommendations. To the authors’ knowledge, the obtained results represent the largest NR V2X SL link level dataset openly available.

Connected Automated Vehicles (CAVs) will use multiple V2X services to support connected and automated driving functions. The bandwidth required to support such services will augment as CAVs are gradually deployed. It is therefore important to accurately estimate the spectrum requirements to anticipate possible scalability challenges ahead. Current estimations consider a simplified modeling of the transmitter as well as context factors such as the number of vehicles in the communication range. Moreover, they do not accurately model if the Quality of Service (QoS) of the considered V2X services is satisfied or not. This study progresses the state of the art with a novel analytical model that quantifies the bandwidth required to support multiple V2X services. The model considers the impact of the vehicular context, the transmission parameters and the communication requirements to take into account the QoS at the receiver. This is important since adapting the transmission parameters can reduce the channel load but also impacts the probability to correctly receive each packet and therefore the bandwidth required to guarantee a target QoS at the receiver. The proposed model can be adapted to different wireless technologies and messages, but is applied in this study to quantify the bandwidth required by LTE-V2X to support the transmission of CAMs, CPMs and MCMs. The study demonstrates the scalability challenges ahead to support multiple V2X services.

The Internet of Vehicles (IoV) will interconnect vehicles, vulnerable road users, and infrastructure nodes for a safer, more efficient, and digitalized mobility. In the IoV vision, traditional network-based communications will be complemented with direct Sidelink (SL) Vehicle-to-Everything (V2X) communications. To this aim, 3GPP introduced in Release 16 the New Radio (NR) V2X SL technology. The NR V2X SL standard includes important Physical (PHY) layer novelties with respect to LTE V2X SL and NR Uplink/Downlink, and is characterized by a large set of configurable parameters. However, existing NR V2X SL link level studies focus on a confined set of configurations. This limits a thorough understanding of the NR V2X SL link level performance and impacts the accuracy of system level evaluations, which typically leverage link level models to accurately represent the PHY layer performance. These models are based on Look-Up Tables (LUTs) that map the link level performance, e.g., BLock Error Rate (BLER), as a function of the link quality, e.g., Signal-to-Noise Ratio (SNR). This study presents an exhaustive NR V2X SL link level evaluation that analyzes the impact of relevant PHY layer aspects, e.g., modulation and coding scheme, channel model, and transmitter-receiver relative speed, considering the wide set of configurations recommended by 3GPP and ETSI. The obtained standard-compliant LUTs are openly released, representing the largest NR V2X SL link level dataset available. The released dataset represents a valuable asset for the community, as it allows exhaustive NR V2X SL system level investigations under a broad range of settings and configurations.

Teleoperated driving (ToD) can support autonomous driving under complex or unexpected traffic scenarios that an autonomous vehicle may not understand or be able to handle. In ToD, autonomous vehicles transmit video feeds and perception data to the remote control center. The operator uses this data to understand the driving environment and remotely control the vehicle that can take over the control once the scenario is resolved. ToD requires reliable and low latency communications between the vehicle and the ToD control center. This study analyzes the feasibility to support ToD with 5G networks. The study demonstrates that the feasibility strongly depends on the bandwidth and the Time Division Duplexing (TDD) frame structure that conditions how the bandwidth is distributed between uplink and downlink transmissions. The study also shows that scaling the number of 5G-supported ToD vehicles requires the vehicles to reduce the video bitrates. The study also shows that traditional centralized 5G network deployments may be challenged by some of the most stringent ToD latency requirements due to the latency introduced by the Internet connection to the ToD control center.

Cooperative perception (a.k.a. Collective perception or cooperative sensing) will allow Connected and Automated Vehicles (CAVs) to share information about detected objects. Cooperative perception improves the sensing accuracy, confidence and range of CAVs, and extends their perception of the driving environment. First message generation rules based on the mobility and dynamics of detected objects have been proposed to decide when a cooperative perception message should be generated and what information it should include. Studies have shown that this type of generation rules can compromise the scalability of cooperative perception and vehicular networks, as they tend to transmit significant amounts of redundant information and generate small and frequent cooperative perception messages that increase the communications overhead. To combat these inefficiencies, this paper proposes and evaluates three techniques that combine, for the first time, baseline mobility-based generation rules for cooperative perception messages with mechanisms to control the redundancy and organize the information about detected objects in order to avoid the frequent transmission of small messages. This study demonstrates that the proposed techniques improve the perception of CAVs and reduce the information age. In addition, the techniques reduce the channel load and improve the scalability of cooperative perception services and vehicular networks. The study demonstrates that the most effective technique is based on: (1) first applying the generation rules to decide whether a cooperative perception message should be generated, (2) then applying redundancy control, and finally (3) organizing the information about all detected objects to avoid small and frequent messages.

5G NR V2X complements LTE V2X to support advanced V2X services for connected and automated driving. 5G NR V2X introduces novel features at the MAC layer that are designed to cope with potential packet collisions, and that could help address the LTE V2X MAC inefficiencies observed under aperiodic traffic of variable size. This is the case of the re-evaluation mechanism that is a mandatory MAC feature of 5G NR V2X, and that seeks to avoid possible packet collisions detected before a vehicle transmits in selected resources. Evaluations conducted to date of 5G NR V2X do not consider the re-evaluation mechanism, and have focused on traffic patterns that do not fully account for the traffic variability of advanced V2X services. This paper extends the current state of the art with the first evaluation of a fully standard compliant 5G NR V2X implementation under the traffic patterns recommended by 3GPP for advanced V2X services. Our study shows that 5G NR V2X mode 2 still faces MAC challenges when using semi-persistent scheduling (SPS) to efficiently support aperiodic traffic of variable size.

Cellular networks usually support non-safety-critical V2X services using Vehicle-to-Network (V2N) connections. However, the flexibility and capabilities of 5G have triggered interest in analyzing whether 5G could also support advanced V2X services using Vehicle-to-Network-to-Vehicle (V2N2V) connections instead of direct Vehicle-to-Vehicle (V2V) connections. V2N2V requires the integration of the 5G network with computing platforms for processing the V2X packets. The flexibility introduced by 5G facilitates the integration with multiple computing platforms such as Multi-access Edge Computing (MEC), edge cloud, shared data center or central cloud. This results in alternative 5G network deployments with the computing platform installed at different locations between the base station and the Internet. These deployments can have important technical implications for supporting V2X services. In this study, we analyze the impact of different 5G and computing platform deployments on the end-to-end (E2E) latency of V2N2V communications under multi-MNO (Mobile Network Operator) scenarios since vehicles may be served by different operators. We also identify which deployment strategies are more suitable to meet the latency requirements of V2X services for connected and automated driving.

5G and multi-access edge computing (MEC) are being considered to support V2X services demanding low latency and highly reliable communications using V2N2V (Vehicle-to-Network-to-Vehicles) communications instead of direct or sidelink V2V (Vehicle-to-Vehicle). Guaranteeing V2X service continuity using V2N2V is a challenging task in multi-Mobile Network Operator (MNO) deployments where vehicles are supported by different MNOs. MEC federations have been proposed to address some of these challenges. A MEC federation is a federated model of MEC systems enabling shared usage of MEC services and applications. Through MEC federations, vehicles can seamlessly access V2X applications independently of whether they are hosted on their MNO’s MEC, or on the MEC of a different (but federated) MNO. This paper presents the first study that analyses the impact of MEC federation on the end-to-end (E2E) latency when supporting V2X services using 5G V2N2V in multi-MNO scenarios. The paper also evaluates the feasibility to support the latency requirements of advanced V2X services in these scenarios, and the benefits introduced by MEC federation. This study considers the V2Xbased cooperative lane merge service as a case study.

5G NR V2X introduces novel MAC features to support advanced V2X services for connected and automated driving. One of these features is the re-evaluation mechanism designed to detect and avoid packet collisions. The re-evaluation mechanism checks before every transmission if the selected resources are still available. If another vehicle has selected the same resources, the re-evaluation mechanism triggers a reselection of resources. The 3GPP standard defines different strategies for vehicles to decide when to perform a re-evaluation check, and how many times a re-evaluation check should be executed before the transmission of a packet. This study evaluates for the first time the impact of two standard strategies on the operation and performance of NR V2X mode 2. The evaluation demonstrates that the two strategies offer a balance between transmission latency and computational cost. We then propose an alternative re-evaluation check strategy that can simultaneously reduce the transmission latency and computational cost without actually degrading the reliability of NR V2X mode 2 transmissions.

Automated driving is now possible in diverse road and traffic conditions. However, there are still situations that automated vehicles cannot handle safely and efficiently. In this case, a Transition of Control (ToC) is necessary so that the driver takes control of the driving. Executing a ToC requires the driver to get full situation awareness of the driving environment. If the driver fails to get back the control in a limited time, a Minimum Risk Maneuver (MRM) is executed to bring the vehicle into a safe state (e.g., decelerating to full stop). The execution of ToCs requires some time and can cause traffic disruption and safety risks that increase if several vehicles execute ToCs/MRMs at similar times and in the same area. This study proposes to use novel C-ITS traffic management measures where the infrastructure exploits V2X communications to assist Connected and Automated Vehicles (CAVs) in the execution of ToCs. The infrastructure can suggest a spatial distribution of ToCs, and inform vehicles of the locations where they could execute a safe stop in case of MRM. This paper reports the first field operational tests that validate the feasibility and quantify the benefits of the proposed infrastructure-assisted ToC and MRM management. The paper also presents the CAV and roadside infrastructure prototypes implemented and used in the trials. The conducted field trials demonstrate that infrastructure-assisted traffic management solutions can reduce safety risks and traffic disruptions.

5G offers high flexibility at the radio, transport and core networks to support various services of critical verticals such as connected and automated driving. At the Radio Access Network (RAN), 5G defines a New Radio (NR). 5G NR utilizes different subcarrier spacing, slot durations, modulations and channel coding schemes. This flexibility offers the possibility to support automotive services with different and demanding requirements, such as Advanced Driver-Assistance System (ADAS), cooperative driving, and remote driving. Previous studies showed that 5G NR can be configured to achieve latencies below 2 ms. However, existing studies are generally restricted to scenarios with a limited number of users and unlimited bandwidth. Therefore, it is important to analyze whether 5G NR can effectively support these services as the network scales under limited spectrum allocations. This study advances the current state of the art to demonstrate that the capability of 5G NR RAN to support advanced V2X services depends on the RAN configuration (subcarrier spacing, slot duration and error protection) and network load.

Factories are evolving into fully digitalized and networked structures for more adaptive and agile production ecosystems in the context of the Industry 4.0. Wireless communications will be a technical pillar of this evolution as it improves the reconfigurability of factories and the integration of mobile robots and objects. The integration of industrial wireless networks into the Industry 4.0 requires solutions capable to support highly reliable and deterministic low latency communications. This is particularly challenging for mobile industrial applications with constantly changing link quality conditions. This article experimentally evaluates for the first time the capacity of diversity and redundancy to improve the reliability and latency of wireless networks for mobile industrial applications. To this aim, a prototype is built in a collaborative robotics experimental facility. The prototype wirelessly connects a dual-arm robot and a mobile robot that collects and supplies components to the dual-arm robot. The prototype implements redundancy and diversity (using multipath TCP) for the wireless connections between both robots. The conducted trials show that both techniques improve the reliability of mobile industrial wireless communications even under the presence of interference. However, redundancy achieves lower latency levels and represents then the most attractive solution to support mobile industrial applications.

Industrial wireless communications will be an important technology enabler for the Industry 4.0 paradigm. However, the pervasive introduction of wireless communications in factories requires improving their reliability and capacity to support low latency communications. An approach to do so is through the introduction of redundancy. Several studies have analytically and through simulations demonstrated the benefits of exploiting redundancy in industrial wireless communications. This paper progresses the current state of the art by experimentally analyzing for the first time the benefits that redundancy in industrial wireless communications can provide to support mobile industrial applications. The analysis has been conducted in a collaborative robotics experimental facility under the framework of the H2020 AUTOW ARE project.

The IEEE 802.11p standard has been created for vehicle to vehicle and vehicle to infrastructure communications. Vehicular networks require vehicles to periodically broadcast beacons in order to detect nearby vehicles or road infrastructure nodes and exchange critical information. The IEEE 802.11p standard defines different data rates that can be used for such transmissions, but 6 Mbps has been generally assumed as the default data rate. Limited efforts have been conducted to date to demonstrate whether 6 Mbps is the optimum data rate or not. This study addresses this issue, and demonstrates by means of simulations and field experiments that 6 Mbps is not (always) the optimum data rate for beaconing in vehicular networks. The conclusions are validated in both urban and highway environments.

Device-centric wireless networks, including Device-to-Device communications and Multi-hop Cellular Networks, are expected to be a relevant component of future 5G wireless networks. Traditionally, opportunistic networking has been proposed for disconnected networks that cannot always reliably ensure real-time end-to-end connections. However, previous studies have demonstrated that opportunistic schemes can also be utilized in connected networks to improve their efficiency by intelligently exploiting context- and content-awareness. In this context, this paper proposes and evaluates a mechanism to select the adequate configuration of opportunistic cellular communications in single-hop and multi-hop cellular networks. To this aim, the mechanism probabilistically identifies for each communications mode the adequate times for cellular transmissions to take place in order to reduce the cellular channel occupancy and improve its capacity. The obtained results show that the proposed scheme reduces the channel occupancy of cellular transmissions for delay-tolerant information by up to 70% compared to conventional single-hop cellular communications.

Device-centric wireless networks, and in particular Multi-hop Cellular Networks (MCN), can improve the capacity and efficiency of wireless networks, and will hence represent a significant element of the 5G ecosystem. Additional gains can be achieved for mobile delay tolerant services when integrating opportunistic networking in device-centric wireless networks. This paper proposes a solution for such integration that is evaluated for the case of 2-hop uplink opportunistic MCN communications. The proposed solution takes into to account the fact that mobile relays might not always be available at the optimum location and time instant, and the fact that sufficient cellular radio resources might not be available when mobile relays want to start forwarding the information towards the base station. The conducted study shows that the proposed scheme can reduce the energy consumption by more than 80% compared to traditional single-hop cellular communications.

Relaying technologies can help address the capacity and energy-efficiency challenges faced by cellular networks as a result of the rapid increase in mobile data consumption. A non-negligible portion of such consumption corresponds to delay tolerant services. This delay tolerance offers the possibility for opportunistic networking to exploit contact opportunities between mobile devices in order to reduce the impact of data traffic on the cellular capacity and energy-efficiency without sacrificing the end-user quality of service. In this context, this paper investigates the use of opportunistic forwarding in MCN-MR (Multi-hop Cellular Networks with Mobile Relays) to reduce energy consumption in the case of delay tolerant services. The study proposes to exploit context information provided at a low cost by the cellular infrastructure to efficiently select the forwarding node in a two-hop MCN-MR scenario. The proposed solution results in significant energy savings compared to traditional single-hop cellular communications and other forwarding solutions reported in the literature.

Multi-hop Cellular Networks using Mobile Relays (MCN-MRs) are being investigated to help address certain limitations of traditional single-hop cellular communications. The MCN-MR benefits depend on the probability to find adequate mobile relays, and on the design of mode selection schemes capable to identify the optimum connection mode. The probability to find adequate mobile relays can be significantly enhanced for delay tolerant services through the adoption of mobile opportunistic networking that exploits the store, carry and forward paradigm. In this context, this paper proposes and evaluates the first mode selection scheme that integrates opportunistic networking into MCN-MR. The obtained results demonstrate that the proposed scheme helps achieve the expected QoS and energy benefits that opportunistic networking can bring to multi-hop cellular networks.

Multi-hop Cellular Networks have recently emerged as a promising technology to overcome the current limitations of cellular systems through the integration of cellular and ad-hoc networking technologies. Several studies have addressed the challenges of Multi-hop Cellular Networks based on Mobile Relays, and demonstrated their performance and potential to improve the user-perceived Quality of Service. However, most of these studies are based on analytical and simulation techniques, and there is yet the need for field tests that confirm their performance. In this context, this paper introduces a novel testbed to investigate Multi-hop Cellular Networks using Mobile Relays through field testing. In addition, this paper also presents the first field test results that demonstrate the performance improvements that can be achieved with Multi-Hop Cellular Networks over traditional cellular systems.

Multi-hop wireless mesh networks, including multi-hop cellular networks, base their operation on the establishment of multi-hop paths to route the information from source to destination. To this aim, it is crucial to define adequate neighbor selection techniques that choose the most appropriate nodes over which to route the information. In this context, this paper proposes a set of neighbor selection techniques that exploit spatial diversity to improve the performance and operation of multi-hop wireless mesh networks.

Multi-hop Cellular Networks using mobile relays require efficient multi-hop networking protocols that provide a high end-to-end performance and reduce the terminal's energy consumption. In this context, this paper proposes a set of novel multi-hop routing protocols that exploit the location of the destination node to reduce their network signalling and overall energy consumption. These two aspects are crucial factors to progress towards the future implementation of Multi-hop Cellular Networks based on mobile relays.