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 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.

5G is a fundamental technology for the digitalization of smart manufacturing. Smart manufacturing relies on the use of digital models to optimize industrial processes before implementation on the manufacturing plants. These models should account for the impact of 5G communications to adequately dimension and optimize 5G-based industrial processes. This paper presents the first integration of industrial digital models with a 5G digital model, implemented as an Asset Administration Shell (AAS) of a 5G system. The two models are interconnected using an OPC UA-based interface. We evaluate the impact of the integrated model using a use case where Automated Guided Vehicles (AGVs) transport material from a warehouse to production lines. The AGVs periodically exchange their positions over 5G to avoid potential collisions. If the communications fail, the AGVs stop for safety reasons until a reliable 5G connection can be guaranteed. We demonstrate that, by integrating 5G and industrial digital models, it is possible to account for, and quantify, the impact of 5G communications on the operation and productivity of industrial processes. This result highlights the importance and necessity of integrating 5G into industrial digital models for their joint design and optimization.

5G is a fundamental technology for the full digitalization of smart manufacturing. The use of Asset Administration Shells (AAS) can facilitate the integration of 5G with Industry 4.0 systems and applications while minimizing the complexities associated with the 5G network management. This study presents the design and implementation of the first full 5G system AAS that is openly released to the community [1]. It includes a 5G UE (User Equipment) AAS and a 5G NW (network) AAS that have been designed following the 5G-ACIA guidelines as well as the Plattform Industrie 4.0 and 3GPP standards. The AASs have been defined to provide and expose the data and capabilities of 5G necessary to facilitate the integration of 5G with Industry 4.0 systems and applications.

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.

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.

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.

5G and beyond networks can facilitate the digital transformation of manufacturing and support more flexible and reconfigurable factories with ubiquitous mobile connectivity. This requires integrating 5G networks with industrial networks that increasingly rely on TSN (Time Sensitive Networking) to support deterministic communications with bounded latencies. Deterministic communications are critical for many industrial applications, but 5G does not natively support deterministic communications. To address this limitation, this study proposes the coordination of the 5G and TSN schedulers and presents a novel 5G configured grant scheduling scheme to support TSN traffic. The scheme uses information about the characteristics of the TSN traffic (packet size, periodicity, and arrival time) to coordinate its scheduling decisions with the TSN scheduler. The study demonstrates that the proposed scheme outperforms the state-of-the-art in the capacity to support multiple TSN traffic flows with different periodicities.

Industry 4.0 and 5.0 applications will contribute towards safer, zero-defect and customized production environments. Such applications (e.g. digital twins, collaborative robotics and extended reality) require communication networks capable to satisfy stringent latency, bandwidth, and reliability requirements. Such requirements can be sustained with 5G networks and their evolution that offer unprecedented communications performance and flexibility thanks to the softwarization of networks and the use of network slicing. Network slicing creates different logical partitions or slices of the common network infrastructure and configures each slice to the requirements of the applications it will support. RAN (Radio Access Network) slicing is a fundamental part of network slicing in 5G as the radio channel is prone to errors and this impacts the capacity to support stringent reliability requirements. To date, RAN slices have been created considering the number of radio resources that must be reserved to guarantee the transmission rate or bandwidth demanded by the applications they will serve. This study demonstrates that this design approach cannot guarantee satisfying the reliability requirements of industrial applications and proposes a novel RAN slice descriptor that takes into account both the reliability and transmission rate requirements of the applications.

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 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.

Cooperation to access wireless networks is a key approach towards optimizing the use of finite radio spectrum resources in overcrowded unlicensed bands and to help satisfy the expectations of wireless users in terms of high data rates and low latency. Although solutions that advocate this approach have been widely proposed in the literature, they still do not consider a number of aspects that can improve the performance of the users’ connections, such as the inclusion of (1) cooperation among network operators and (2) users’ quality requirements based on their applications. To fill this gap, in this paper we propose a centralized framework that is aimed at providing a “win‐win” cooperation among Wi‐Fi and cellular networks, which takes into account 5G technologies and users’ requirements in terms of Quality of Service (QoS). Moreover, the framework is supported by smart Radio Access Technology (RAT) selection mechanisms that orchestrate the connection of the clients to the networks. In particular, we discuss details on the design of the proposed framework, the motivation behind its implementation, the main novelties, its feasibility, and the main components. In order to demonstrate the benefits of our solution, we illustrate efficiency results achieved through the simulation of a smart RAT selection algorithm in a realistic scenario, which mimics the proposed “win‐win” cooperation between Wi‐Fi and cellular 5G networks, and we also discuss potential benefits for wireless and mobile network operators.

Time Sensitive Networking (TSN) is becoming the standard Ethernet-based technology for converged networks of Industry 4.0 due to its capacity to support deterministic latency requirements. However, it cannot provide the required flexibility to support mobile industrial applications required for the factories of the future. This could be enabled through the integration of wireless technologies in factories, and in particular of 5G and Beyond networks since they have been designed to support ultra-reliable and low-latency communications. This has triggered significant interest to integrate 5G and TSN networks, and first frameworks for such integration have been defined. However, the work is at early stages and the solutions to effectively integrate the two networks so that 5G can support TSN QoS levels are yet to be designed. This paper discusses current research and standardization work on 5G-TSN integration, and quantifies for a closed loop control application the 5GS bridge delay. The paper uses an example based on 5G-ACIA [1] to discuss open technical and research challenges to effectively integrate 5G and TSN.

5G networks can support the development of the Industry 4.0. To this aim, 5G must be able to guarantee the deterministic latency requirements that characterize many industrial applications. This objective can be achieved using network slicing, a novel 5G paradigm that exploits the softwarization of networks to create different logical instances of the network over a common network infrastructure. Each instance is configured to support specific applications. Slicing can be applied at the Core Network or at the Radio Access Network (RAN). This study focuses on RAN slicing since the RAN typical accounts for a large part of the end-to-end delay. RAN slicing splits (and configures) resources at the RAN level between the slices in order to adequately serve nodes with a particular profile. This includes identifying the necessary radio resources per slice. To date, most proposals define slices in terms of the number of required radio resources. While this descriptor can account for bandwidth or rate requirements, it does not adequately reflect the latency requirements characteristic of many Industry 4.0 applications. This paper proposes a novel latency-based RAN slice descriptor and demonstrates that the new descriptor improves the capacity of RAN slicing to meet the latency requirements of Industry 4.0 applications with deterministic periodic traffic.

Industry 4.0 will interconnect and digitalize traditional industries to enable smart and adaptable factories that efficiently utilize resources and integrate systems. A key enabler of this paradigm is the communications infrastructure that will support the ubiquitous connectivity of cyber-physical production systems. The integration of wireless networks will facilitate the dynamic reconfiguration of the factories of the future, and the collection and management of large amounts of data. This vision requires reliable and low latency wireless links with the necessary bandwidth to support data intensive applications and spatio-temporal variations of data resulting from the reconfiguration of Industrial IoT (Internet of Things) systems. To this aim, this paper proposes a load balancing scheme that dynamically manages the wireless links based on their quality and the amount of data to be transmitted by each node. The proposed scheme avoids the saturation of channels, and significantly augments the reliability of industrial wireless networks in comparison with existing solutions.

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.

Device-to-Device (D2D) communications can increase the spectral efficiency of future cellular networks when sharing part of the cellular spectrum. Radio resource allocation mechanisms are then necessary to control the interference that D2D and cellular transmissions can generate to each other. Most of the existing allocation schemes rely on the knowledge of the channel gain of all possible links between cellular and D2D nodes. This paper proposes to reduce the complexity cost and signalling overhead of the allocation process by using location information available at the network level. Using this information, the base station assigns radio resources to new D2D transmissions with the objective to control and limit the interference to the primary cellular users and existing D2D transmissions. The proposed radio resource allocation scheme continuously monitors that the user QoS requirements are satisfied. If it is not the case, it dynamically modifies the resource allocation to the interfering D2D transmissions. The proposed scheme achieves performance levels similar to that obtained with an optimized centralized allocation scheme, but with a significantly lower complexity cost and signaling overhead.

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.

The study and design of Joint Radio Resource Management (JRRM) techniques is a key and challenging aspect in future heterogeneous wireless systems where different Radio Access Technologies (RAT) will physically coexist. In these systems, the total available radio resources need to be used in a coordinated way to guarantee adequate satisfaction levels to all users, and maximize the system revenues. In addition to carry out an efficient use of the available radio resources, JRRM algorithms need to exhibit good computational performance to guarantee their future implementation viability. In this context, this paper proposes novel JRRM techniques based on linear programming techniques, and investigates their computational cost when implemented in DSP platforms commonly used in mobile-based stations. The obtained results demonstrate the feasibility to implement the proposed JRRM algorithms in future heterogeneous wireless systems.

Beyond 3G wireless systems will be composed of a variety of radio access technologies (RATs) with different, but also complementary, performance and technical characteristics. To exploit such diversity while guaranteeing the interoperability and efficient management of the different RATs, common radio resource management (CRRM) techniques need to be defined. This work proposes and evaluates a CRRM policy that simultaneously assigns to each user an adequate combination of RAT and number of radio resources within such RAT to guarantee its QoS requirements. The proposed CRRM technique is based on linear objective functions and programming tools.

Multi-channel operation in wireless systems has been proposed to increase user throughput and reduce transmission delays. However, multi-channel operation requires adequate resource allocation policies to guarantee user fairness and avoid channel access stagnation. The definition of such policies is particularly challenging in heterogeneous traffic scenarios where each traffic service has different quality of service requirements. In this context, this work proposes and evaluates various multi-channel radio resource distribution policies designed to operate under heterogeneous traffic environments. In particular, this paper proposes the application of bankruptcy policies to guarantee user fairness, and compares their performance to other schemes. The proposed policies can also be extended to manage radio resources in heterogeneous wireless systems.