OPE1 – Operational & Experimental Insights
Wednesday, 3 June 2026, 8:30-10:00, room Sala 12 (1st floor)
Session Chair: David Gomez-Barquero (Univ. Politecnica de Valencia, ES)
Interaction-Aware QoS-Flow Switching on Haptic Teleoperation Scenarios over 5G SA Networks
Fernando Hernandez-Gobertti (Universitat Politècnica de València, Spain); Daniel Rodriguez-Guevara (Technical University of Munich, Germany); David Gomez-Barquero (Universitat Politecnica de Valencia, Spain); Eckehard Steinbach (Technische Universität München, Germany)
Tactile Internet applications require ultra-low end-to-end latency and tightly bounded jitter, especially in the distribution tails, to preserve kinaesthetic stability and perceived realism. Although 5G Standalone (SA) supports differentiated treatment, dynamic interaction regimes can still trigger brief, contact-induced traffic bursts that worsen tail behavior. We present an interaction-aware resource-allocation framework for kinaesthetic communication encoded with the IEEE 1918.1.1-2024 codec. A lightweight real-time classifier infers the user’s interaction state with virtual objects (static, free-air movement, tapping, holding, dragging) directly from the 3D Systems Touch signal stream. The inferred state drives a closed-loop controller whose runtime action is restricted to an operator-safe mechanism: switching the haptic stream among pre-provisioned 5G SA QoS flows mapped to distinct scheduling priorities via packet-filter binding within an existing PDU session. We implement the framework on an end-to-end 5G SA testbed integrating a commercial RAN and a 5G Core, and evaluate it across indoor and outdoor deployments. Using synchronized one-way E2E timing and ablations against fixed-profile baselines, we show that gains concentrate in contact-rich states: for tapping, the interaction-aware policy tightens p95 latency from 13.4 ms to 6.1 ms indoors and from 15.1 ms to 7.2 ms outdoors, while reducing p99 from 19.2 ms to 8.7 ms and from 22.0 ms to 10.4 ms, respectively. Low-demand states remain essentially unchanged. These results quantify how standards-aligned QoS-flow selection impacts kinaesthetic performance and provide a deployable path to self-adaptive haptic communication on current 5G SA systems.
Over-the-Air Absolute Time Synchronization in 5G Sidelink Networks
Jakob Arndt (Missing Link Electronics GmbH & Technische Universität Berlin); Frederik Pfautsch (Massive Beams, Germany & Missing Link Electronics GmbH); Kenan Turbic (Fraunhofer HHI, Germany); Ulrich Langenbach (Missing Link Electronics GmbH, Germany); Slawomir Stanczak (Technische Universität Berlin & Fraunhofer Heinrich Hertz Institute, Germany)
Time of Day (ToD) synchronization is critical for applications such as robotic assembly lines, autonomous driving, and distributed sensor networks. 5G sidelink networks currently lack mechanisms for sub-microsecond ToD synchronization, forcing communicating devices to rely on external solutions such as Global Navigation Satellite System (GNSS). This work addresses this gap by examining over-the-air ToD synchronization via 5G sidelink. A ToD synchronization scheme based on the widely used Round-Trip Time method is implemented and evaluated on a Software Defined Radio-based setup. It is demonstrated that the implemented algorithm achieves an accuracy of 66 ns and a precision of 60 ns in the considered fading-free case. The results remain consistent with the propagation delay between end devices increasing, thus outperforming the methods relying only on the existing sidelink physical layer synchronization. Additional simulation results indicate that the algorithm is robust against challenging channel conditions, characterized by high noise and obstructed Line of Sight.
An ORIGAMI Use-Case Validation via 6G-SANDBOX Experimentation
Dena Markudova (Telefonica Research, Spain); Viktoria Vomhoff (University of Würzburg, Germany); Stefan Geissler (University of Wuerzburg, Germany); Matteo Pagin (Keysight Technologies, Denmark); Steffen Gebert (EMnify GmbH, Germany); Arturo Jose Torrealba Ferrer (Telefonica Innovacion Digital, Spain); Dimitris Tsolkas (Fogus Innovations and Services & National and Kapodistrian University of Athens, Greece); Pablo Herrera Diaz (University of Malaga, Spain); Andres Garcia-Saavedra (NEC Laboratories Europe, Germany); Andra Lutu (Telefónica Research, Spain)
The transition to 6G presents many barriers to be overcome, as well as opportunities for innovation.
The integration of Network Intelligence (NI) is pivotal in optimizing network performance, enhancing security, and improving resource allocation. The ORIGAMI project identifies 8 critical barriers towards 6G deployment, and proposes both architectural and NI innovations to overcome them. This paper discusses experimentation with one use-case that implements one such architectural innovation — namely, the Global Operator Model that leverages the Global Service-Based Architecture (GSBA). In particular, we focus on the use of the 6G-SANBDOX infrastructure to allow for proof-of-concept implementations of the GSBA. Overall, this paper serves as an example of how ORIGAMI’s approach to innovation benefits from state-of-the-art experimental platforms available via the 6G-SANDBOX project — thus highlighting the importance of joint architecture design and experimentation efforts.
Design, Implementation, and Evaluation of a Live ML-Based Communication Parameters Optimization Solution for LoRaWAN
Amila Wimalaweera, Konstantin Mikhaylov and Tuomo Hänninen (University of Oulu, Finland)
Long-range wide area network (LoRaWAN) is widely used for energy-constrained internet of things (IoT) applications, yet its performance under dynamic channel conditions is limited by slowly adapting control mechanisms. Although machine learning (ML) has been proposed to address these challenges, most existing work is based on simulations rather than real deployments. This paper provides a two-fold contribution: first, it introduces and discusses the challenges related to the implementation of a practical LoRaWAN testbed that enables real-time integration and evaluation of ML-based communication-parameter control in an operational network; second, it presents a lightweight convolutional neural network-based adaptive data rate (ADR) algorithm implemented at the network server, which predicts suitable spreading factor values from recent uplink metadata without adding computational load to end devices. Trained on real measurements from RN2483 devices in the University of Oulu 5G Test Network and evaluated under controlled attenuation, the proposed approach improves the packet success rate by 50% compared to the standard ADR. Overall, the work demonstrates the feasibility of deploying ML-driven control directly in live LoRaWAN environments and establishes a foundation for future studies beyond simulation-based analyses.
On-Demand Beyond-5G Network and Mission Critical Services for PPDR Scenarios
José Vicente de Oliveira (Instituto de Telecomunicações, Portugal & Universidade de Aveiro, Portugal); Pedro Valente (Universidade de Aveiro, Portugal & Instituto de Telecomunicações, Portugal); Duarte Raposo (Instituto de Telecomunicações, Portugal); Pedro Rito (University of Aveiro, Portugal & Instituto de Telecomunicações, Portugal); Miguel Luis (Instituto Superior Técnico & Instituto Telecomunicacoes, Portugal); Susana Sargento (Universidade de Aveiro, Portugal); Carlos Marques and Miguel Mesquita (Altice Labs, Portugal); Filipe Cabral Pinto (Alticelabs, Portugal); Alexandre Moron (Airbus, France)
Recent natural disasters, including severe storms, wildfires, and prolonged power outages, have highlighted the vulnerability of telecommunication infrastructures. Public Protection and Disaster Relief (PPDR) services are critical in such scenarios, requiring quick and reliable communication networks to ensure effective response and coordination. This work presents an on-demand 5G and Non-Terrestrial Network (NTN) connectivity architecture that combines an open-source non-public flying network with a proprietary Mission Critical platform (MCX), addressing the requirements of both affected civilians and First Responders. The open-source Non-Public Network (NPN) is mounted on an Unnamed Aerial Vehicle (UAV), and is built with Open5GS and IMS-based voice services using Kamailio. It provides essential services for people impacted in the disaster, including Voice over New Radio (VoNR) and QoS differentiation. The architecture also supports roaming, allowing users to authenticate via the operator’s Home Network, while connecting to the local on site Visited Network using the Local Breakout approach. This reduces latency and inefficient backhauling of user-plane traffic. For PPDR teams and other disaster response teams, the MCX solution complements the NPN by providing resilient mission-critical voice, video and data services through a cloud-native microservice architecture, suitable for deployment in edge nodes on the field. Experimental results demonstrate that the proposed open-source 5G NPN can support communications in disaster scenarios, sustaining up to 32 simultaneous VoNR calls with a MOS score of 4.5, while interoperating with an MCX platform for first-responder coordination, enhancing both service availability and traffic prioritization.
