arXiv subjects

M. Carmen Lucas-Estañ

Publications and source records attributed to M. Carmen Lucas-Estañ.

12 recordsLinked to original sources

arXiv2026

Latency-Sensitive 5G RAN Slicing for Industry 4.0

Network slicing is a novel 5G paradigm that exploits the virtualization and softwarization of networks to create different logical network instances over a common network infrastructure. Each instance is tailored for specific Quality of Service (QoS) profiles so that network slicing can simultaneously support several services with diverse requirements. Network slicing can be applied at the Core Network or at the Radio Access Network (RAN). RAN slicing is particularly relevant to support latency-sensitive or timecritical applications since the RAN accounts for a significant part of the end-to-end transmission latency. In this context, this study proposes a novel latency-sensitive 5G RAN slicing solution. The proposal includes schemes to design slices and partition (or allocate) radio resources among slices. These schemes are designed with the objective to satisfy both the rate and latency demands of diverse applications. In particular, this study considers applications with deterministic aperiodic, deterministic periodic and nondeterministic traffic. The latency-sensitive 5G RAN slicing proposal is evaluated in Industry 4.0 scenarios where stringent and/or deterministic latency requirements are common. However, it can be evolved to support other verticals with latency-sensitive or time-critical applications.

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arXiv2026

Common Radio Resource Management Policy for Multimedia Traffic in Beyond 3G 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.

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arXiv2026

5G Configured Grant Scheduling for 5G-TSN Integration for the Support of Industry 4.0

Factories are evolving towards digitalized data-based ecosystems under the paradigm of the Industry 4.0 where new industrial services allow the implementation of more robust, resilient and customized manufacturing systems. Such services (e.g., digital twins, extended reality or cooperative robots) will require highly reliable and deterministic communication networks capable of supporting stringent latency and reliability requirements. 5G networks and their future evolution have the necessary capabilities to meet these requirements. However, the use of 5G in industrial environments requires its effective and efficient integration with Time Sensitive Networking (TSN), which is becoming the standard wired technology for Industry 4.0 environments. TSN provides unprecedented deterministic service levels with perfectly bounded latencies. The integration of the industrial 5G and TSN networks will be key to support the flexibility and determinism demanded by the Industry 4.0 paradigm. A critical aspect to achieve this integration is the coordination of the schedulers of both networks. TSN has information about the capabilities of the 5G-TSN integrated network, and it is in charge of deciding the path and scheduling for each TSN traffic flow. The scheduling in 5G must be done according to the scheduling decisions and information provided by TSN to guarantee the end-to-end latency requirements of TSN traffic. In this context, this paper proposes a novel Configured Grant scheduling scheme for 5G integrated into a TSN network that aims to meet the latency requirements of the different TSN flows. The proposed scheme exploits the information provided by TSN about the characteristics of the TSN traffic to coordinate its decision with the scheduling of TSN. This study demonstrates that the proposed scheduling scheme considerably increases the number of TSN flows that can be satisfactorily served.

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arXiv2026

Latency-Sensitive 5G RAN Slicing for Deterministic Aperiodic Traffic in Smart Manufacturing

5G and beyond networks will support the digitalization of smart manufacturing thanks to their capacity to simultaneously serve different types of traffic with distinct QoS requirements. This can be achieved using Network Slicing that creates different logical network partitions (or slices) over a common infrastructure, and each can be tailored to support a particular type of traffic. The configuration of the Radio Access Network (RAN) slices strongly impacts the capacity of 5G and beyond to support critical services with stringent QoS requirements, and in particular deterministic requirements. Existing RAN Slicing solutions only consider the transmission rate (or bandwidth) requirements of the different services to partition the radio resources. This study demonstrates that this approach is not suitable to guarantee the stringent latency requirements of deterministic aperiodic traffic that is characteristic of industrial critical applications. We then propose designing RAN slices using descriptors that consider both the services' transmission rate and latency requirements, and demonstrate that this approach can support critical services that generate deterministic aperiodic traffic.

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arXiv2026

Configured Grant Scheduling for the Support of TSN Traffic in 5G and Beyond Industrial Networks

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.

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arXiv2026

Support of Teleoperated Driving with 5G Networks

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.

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arXiv2026

An open-source implementation and validation of 5G NR Configured Grant for URLLC in ns-3 5G LENA: a scheduling case study in Industry 4.0 scenarios

Factories are undergoing a digital transformation towards cost-efficient, zero-defect manufacturing, creating the need for communication networks capable of meeting stringent latency and reliability requirements. 5G and beyond networks are being designed to support Ultra-Reliable Low-Latency Communications (URLLC). However, the use of dynamic scheduling for uplink transmissions introduces additional latency due to the signaling required to request and allocate radio resources. To reduce this latency, 5G NR defines Configured Grant (CG), which pre-allocates uplink resources and eliminates the need for per-packet scheduling requests. Accurate simulation tools implementing URLLC features are essential to evaluate the capability of 5G networks to support time-critical services and to investigate new solutions. Nevertheless, the availability of such tools is limited and, to the best of the authors' knowledge, no open-source 5G NR simulator currently supports CG. To address this gap, this paper presents the first implementation of CG in an open-source 5G NR simulator. Specifically, CG has been integrated into the ns-3 5G-LENA system-level simulator and made publicly available. In addition, the Orthogonal Frequency Division Multiple Access (OFDMA) implementation has been enhanced to better reflect the flexibility of 5G NR. The implementation is validated through Industry 4.0 scenarios, where the latency performance achieved with CG under different scheduling policies is analyzed. Results show that the latency obtained with 5G-LENA closely matches that reported in previous analytical studies. Furthermore, the study highlights the importance of efficient radio resource utilization to reduce latency and satisfy the requirements of critical industrial services.

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arXiv2026

5G UE and Network Asset Administration Shells for the Integration of 5G and Industry 4.0 Systems

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.

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arXiv2026

Predictive Configured Grant Scheduling for Deterministic Wireless Communications

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.

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arXiv2026

Predictive Dynamic Scheduling for Deterministic Communications in Beyond 5G

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 semi-static 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.

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arXiv2026

Predictive and Spatially Aware Scheduling in Flexible Duplexing for Deterministic Communications

Next generation wireless networks must sustain deterministic service levels for time-sensitive closed-loop applications. Flexible duplexing (FD) is an efficient solution to support these services, as it enables simultaneous uplink (UL) and downlink (DL) transmissions over orthogonal resources within the same band. However, simultaneous UL and DL transmissions can create conflicts that degrade performance due to interference from in-band emissions (IBE) and UL-to-DL cross-link interference (CLI). In this paper, we propose to use traffic forecasting and predictive scheduling to mitigate UL/DL conflicts in FD. Our proposal exploits traffic predictions to increase the likelihood of scheduling CLI-free UL and DL transmissions, and leverages spatial diversity to minimize the impact of unavoidable conflicts. Results show that the proposed scheme reduces UL/DL scheduling conflicts and improves the SINR of conflicted transmissions by more than 5 dB. This leads to gains of over 40% in the number of successfully completed transmissions compared to reference FD schemes.

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arXiv2019

Power and Packet Rate Control for Vehicular Networks in Multi-Application Scenarios

Vehicular networks require vehicles to periodically transmit 1-hop broadcast packets in order to detect other vehicles in their local neighborhood. Many vehicular applications depend on the correct reception of these packets that are transmitted on a common control channel. Vehicles will actually be required to simultaneously execute multiple applications. The transmission of the broadcast packets should hence be configured to satisfy the requirements of all applications while controlling the channel load. This can be challenging when vehicles simultaneously run multiple applications, and each application has different requirements that vary with the vehicular context (e.g. speed and density). In this context, this paper proposes and evaluates different techniques to dynamically adapt the rate and power of 1-hop broadcast packets per vehicle in multi-application scenarios. The proposed techniques are designed to satisfy the requirements of multiple simultaneous applications and reduce the channel load. The evaluation shows that the proposed techniques significantly decrease the channel load, and can better satisfy the requirements of multiple applications compared to existing approaches, in particular the Message Handler specified in the SAE J2735 DSRC Message Set Dictionary.

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