arXiv subjects

Utz Roedig

Publications and source records attributed to Utz Roedig.

14 recordsLinked to original sources

arXiv2026

Scaling 5G-TSN Bridges: Operating Regimes, Scheduling, and Time Synchronisation Under Heterogeneous Industrial Traffic

3GPP Release 16 enables a 5G system to operate as a transparent IEEE 802.1 TSN bridge, but its scalability under heterogeneous industrial workloads remains insufficiently characterised. This paper uses the nascTime framework on OMNeT++/Simu5G to evaluate how many TSN endpoints a single 5G NR cell can bridge before per-flow QoS degrades. We model closed-loop control, machine vision, bulk telemetry, and IEEE 802.1AS traffic over a four-bearer SDAP architec- ture, varying the number of endpoints from 1 to 40, MAC scheduler, radio bandwidth (10 MHz and 20 MHz), and channel model. Results show three operating regimes. Below saturation, non-DRR schedulers perform similarly; near saturation, QoS- aware PF reduces critical-flow P99 latency by up to two or- ders of magnitude relative to channel-aware and fairness-based schedulers; and under overload, only QoS-PF maintains near- complete delivery for the highest-priority traffic. Across the two evaluated bandwidths, the saturation threshold approximately doubles when bandwidth doubles. We also show that isolating IEEE 802.1AS/gPTP traffic on a dedicated high-priority radio bearer reduces clock-servo instability, although endpoints carry- ing lower-priority data still experience elevated synchronisation delay under saturation because of reduced MAC scheduling frequency. Finally, the evaluated sub-6 GHz, 30 kHz-SCS con- figuration exhibits an effective latency floor of approximately 2.25 ms, indicating that sub-3 ms TSN deadlines may require radio-configuration changes such as configured grants or higher numerology

cs.NI↗

arXiv2026

ISAC Privacy: Challenges and Solutions for 6G

Integrated sensing and communication (ISAC) is a promising feature of future communication networks. While spatial sensing can improve network performance and enable external services, it also creates privacy challenges that go beyond the confidentiality of communication content. Future networks using millimeter-wave (mmWave) and sub-terahertz (THz) frequencies may collect or infer detailed information about people, devices, bystanders, passive objects, and environments in a sixth-generation (6G) deployment area. Such sensing can reveal location and environment data, support behavioral profiling such as movement or activity recognition, and, in advanced cases, expose physiological information such as breathing frequency or heart-rate-related data. Thus, the capabilities of spatial sensing must be controlled to satisfy privacy requirements. In this work, we organize privacy-sensitive ISAC data into three sensing levels: location and environment data, behavioral data, and physiological data, and use this classification as the organizing principle throughout the paper. Based on this classification, we discuss internal and external ISAC applications, identify privacy challenges related to consent, transparency, data ownership, profiling, bystander exposure, and sensitive sensing data, review representative solution directions, and outline future research directions for privacy-preserving ISAC.

cs.IT↗

arXiv2026

Post-Cut Metadata Inference Attacks on Quantum Circuit Cutting Pipelines

Quantum cloud providers can identify a user's algorithm and secret problem structure without ever seeing actual quantum data, simply by analyzing routine metadata collected for billing and system management. Existing confidentiality tools such as blind quantum computation and quantum homomorphic encryption protect the quantum payload itself, but they do not protect this classical orchestration metadata. This leaves an unexplored security risk in the logs generated when a large quantum program is split into smaller pieces to fit onto limited hardware, a process known as circuit cutting. These fragments leak sensitive information through what we term the topological transpilation penalty: the unavoidable depth and gate inflation added when a compiler reorganizes a program for a restricted hardware topology. Tests on a 156-qubit production Quantum Processing Unit (QPU) show that traditional timing side-channels fail in this setting, since hardware control-plane delays mask actual quantum execution time. The unique shape of the transpilation penalty acts instead as a persistent structural fingerprint for the hidden workload. Using 12,000 circuit fragments across eight algorithm families, our attack recovers algorithm family and Hamiltonian k-locality with near-perfect accuracy, achieving instance-disjoint AUC = 1.000 for both. This leakage persists under size-holdout evaluation on unseen circuit scales, with AUC = 0.987 and 0.986 respectively. The cutting mechanism is inferred with AUC = 0.991, and hardware topology is recovered well above chance with AUC = 0.818. These results show that circuit cutting exposes algorithmic intent, and potentially proprietary problem structure, through metadata alone, without any need to observe quantum data.

quant-ph↗

arXiv2026

nascTime: A Full-Stack 5G-TSN Bridge Simulation Framework with SDAP-Based QoS Mapping and IEEE 802.1AS Transparent Clock

3GPP Release~16 specifies how a 5G system can operate as a transparent IEEE~802.1 TSN bridge, yet no existing simulation framework implements the complete bridge architecture with end-to-end QoS mapping through the SDAP layer, per-flow Data Radio Bearer selection, and IEEE~802.1AS transparent clock behaviour with measured residence time. Existing tools model either QoS mapping without time synchronisation, or time synchronisation without a data plane. This paper presents nascTime, a simulation framework built on OMNeT++~6.3, INET~4.6, and Simu5G that implements the full 3GPP 5G-TSN bridge model. The NW-TT and DS-TT are realised as modular compound modules that integrate with INET's \texttt{LayeredEthernetInterface} and streaming PHY. QoS mapping traverses the complete PCP\,$\rightarrow$\,DSCP\,$\rightarrow$\,QFI\,$\rightarrow$\,SDAP/DRB pipeline, and gPTP frames are transported through the simulated 5G radio path via L2-in-GTP-U encapsulation with per-message residence-time correction. We validate the framework with a three-endpoint factory topology under both ideal and fading channel conditions. In the ideal scenario, high-priority traffic achieves 99.9\% delivery with a mean end-to-end delay of 2.58\,ms, while the measured 5GS residence time exhibits a variance below 0.2\,$\mu$s. Under a fading channel, residence-time variance increases to 48\,$\mu$s, confirming that the framework captures radio-induced timing effects absent from abstract-delay simulators. nascTime is publicly available and constitutes the first full-stack 5G-TSN bridge simulation with SDAP-based QoS differentiation and measured IEEE~802.1AS transparent clock behaviour.

cs.NI↗

arXiv2025

Surface Acoustic Wave Gas Sensors: Innovations in Functional Materials, Sensing Dynamics, and Signal Analysis

Surface Acoustic Wave gas sensors have garnered increasing attention as highly sensitive, miniaturized, and wireless compatible platforms for molecular detection. Their unique ability to convert surface perturbations into measurable acoustic shifts makes them ideal for gas sensing across diverse environments. This review synthesizes reported SAW platforms across substrates and modes Rayleigh, SH-SAW, Love links transduction pathways to material choice, and benchmarks performance for key analytes, e.g., NO2, NH3, VOCs, CO2, etc. We catalogue nanostructured oxides, polymers, carbon based films, and hybrid heterojunction coatings, highlighting attributes such as porosity, surface chemistry, and interfacial charge transfer that govern sensitivity and reversibility. We also highlight the emerging use of SAW devices to probe adsorption desorption dynamics, offering analyte specific interaction signatures beyond equilibrium, offering a new perspective into analyte specific interaction pathways. Additionally, the integration of machine learning is discussed as a transformative tool for signal decoding, environmental compensation, and adaptive calibration. We also identify key challenges, cross sensitivity, signal drift, material degradation, and deployment at the edge and review recent strategies to address them. Looking ahead, we envision the evolution of SAW platforms into intelligent, autonomous sensing systems with applications in environmental monitoring, industrial process control, and healthcare diagnostics.

physics.app-ph↗

arXiv2025

QoS-Aware Proportional Fairness Scheduling for Multi-Flow 5G UEs: A Smart Factory Perspective

Private 5G networks are emerging as key enablers for smart factories, where a single device often handles multiple concurrent traffic flows with distinct Quality of Service (QoS) requirements. Existing simulation frameworks, however, lack the fidelity to model such multi-flow behavior at the QoS Flow Identifier (QFI) level. This paper addresses this gap by extending Simu5G to support per-QFI modeling and by introducing a novel QoS-aware Proportional Fairness (QoS-PF) scheduler. The scheduler dynamically balances delay, Guaranteed Bit Rate (GBR), and priority metrics to optimize resource allocation across heterogeneous flows. We evaluate the proposed approach in a realistic smart factory scenario featuring edge-hosted machine vision, real-time control loops, and bulk data transfer. Results show that QoS-PF improves deadline adherence and fairness without compromising throughput. All extensions are implemented in a modular and open-source manner to support future research. Our work provides both a methodological and architectural foundation for simulating and analyzing advanced QoS policies in industrial 5G deployments.

cs.NI↗

arXiv2025

SDAP-based QoS Flow Multiplexing Support in Simu5G for 5G NR Simulation

The Service Data Adaptation Protocol (SDAP) plays a central role in 5G New Radio (NR), acting as a bridge between the core and radio networks, by enabling QoS Flow multiplexing over shared Data Radio Bearers (DRBs). However, most 5G simulation frameworks, including the popular OMNet++-based Simu5G, lack SDAP support, limiting their ability to model realistic QoS behavior. This paper presents a modular, standardscompliant SDAP extension for Simu5G. The implementation includes core elements such as QoS Flow Identifer (QFI) flow tagging, SDAP header insertion/removal, and configurable logical DRB mapping. The proposed design supports multi-QFI simulation scenarios and enables researchers to model differentiated QoS flows and flowaware scheduling policies. Validation results confirm correct SDAP behavior and pave the way for advanced 5G simulations involving per-flow isolation, latency-sensitive traffic, and industrial QoS profiles.

cs.NI↗

arXiv2025

Resilient Time-Sensitive Networking for Industrial IoT: Configuration and Fault-Tolerance Evaluation

Time-Sensitive Networking (TSN) is increasingly adopted in industrial systems to meet strict latency, jitter, and reliability requirements. However, evaluating TSN's fault tolerance under realistic failure conditions remains challenging. This paper presents IN2C, a modular OMNeT++/INET-based simulation framework that models two synchronized production cells connected to centralized infrastructure. IN2C integrates core TSN features, including time synchronization, traffic shaping, per-stream filtering, and Frame Replication and Elimination for Redundancy (FRER), alongside XML-driven fault injection for link and node failures. Four fault scenarios are evaluated to compare TSN performance with and without redundancy. Results show that FRER eliminates packet loss and achieves submillisecond recovery, though with 2-3x higher link utilization. These findings offer practical guidance for deploying TSN in bandwidth-constrained industrial environments.

cs.NI↗

arXiv2022

Dynamic Recognition of Speakers for Consent Management by Contrastive Embedding Replay

Voice assistants overhear conversations and a consent management mechanism is required. Consent management can be implemented using speaker recognition. Users that do not give consent enrol their voice and all their further recordings are discarded. Building speaker recognition-based consent management is challenging as dynamic registration, removal, and re-registration of speakers must be efficiently handled. This work proposes a consent management system addressing the aforementioned challenges. A contrastive based training is applied to learn the underlying speaker equivariance inductive bias. The contrastive features for buckets of speakers are trained a few steps into each iteration and act as replay buffers. These features are progressively selected using a multi-strided random sampler for classification. Moreover, new methods for dynamic registration using a portion of old utterances, removal, and re-registration of speakers are proposed. The results verify memory efficiency and dynamic capabilities of the proposed methods and outperform the existing approach from the literature.

cs.SD↗

arXiv2018

SonarSnoop: Active Acoustic Side-Channel Attacks

We report the first active acoustic side-channel attack. Speakers are used to emit human inaudible acoustic signals and the echo is recorded via microphones, turning the acoustic system of a smart phone into a sonar system. The echo signal can be used to profile user interaction with the device. For example, a victim's finger movements can be inferred to steal Android phone unlock patterns. In our empirical study, the number of candidate unlock patterns that an attacker must try to authenticate herself to a Samsung S4 Android phone can be reduced by up to 70% using this novel acoustic side-channel. Our approach can be easily applied to other application scenarios and device types. Overall, our work highlights a new family of security threats.

cs.CR↗

arXiv2018

Strong PUFs from arrays of resonant tunnelling diodes

In this work, we design and implement a strong physical uncloneable function from an array of individual resonant tunnelling diodes that were previously described to have a unique response when challenged. The system demonstrates the exponential scalability of its responses when compared to the number of devices present in the system, with an expected large set of responses while retaining a 1:1 relationship with challenges. Using a relatively small set of 16 devices, 256 responses are shown to have promising levels of distinctness and repeatability through multiple measurements.

physics.app-ph↗

arXiv2017

Optical identification using imperfections in 2D materials

The ability to uniquely identify an object or device is important for authentication. Imperfections, locked into structures during fabrication, can be used to provide a fingerprint that is challenging to reproduce. In this paper, we propose a simple optical technique to read unique information from nanometer-scale defects in 2D materials. Flaws created during crystal growth or fabrication lead to spatial variations in the bandgap of 2D materials that can be characterized through photoluminescence measurements. We show a simple setup involving an angle-adjustable transmission filter, simple optics and a CCD camera can capture spatially-dependent photoluminescence to produce complex maps of unique information from 2D monolayers. Atomic force microscopy is used to verify the origin of the optical signature measured, demonstrating that it results from nanometer-scale imperfections. This solution to optical identification with 2D materials could be employed as a robust security measure to prevent counterfeiting.

cond-mat.mes-hall↗

arXiv2017

Extracting random numbers from quantum tunnelling through a single diode

Random number generation is crucial in many aspects of everyday life, as online security and privacy depend ultimately on the quality of random numbers. Many current implementations are based on pseudo-random number generators, but information security requires true random numbers for sensitive applications like key generation in banking, defence or even social media. True random number generators are systems whose outputs cannot be determined, even if their internal structure and response history are known. Sources of quantum noise are thus ideal for this application due to their intrinsic uncertainty. In this work, we propose using resonant tunnelling diodes as practical true random number generators based on a quantum mechanical effect. The output of the proposed devices can be directly used as a random stream of bits or can be further distilled using randomness extraction algorithms, depending on the application.

quant-ph↗

arXiv2016

Mitigating Inter-network Interference in LoRa Networks

Long Range (LoRa) is a popular technology used to construct Low-Power Wide-Area Network (LPWAN) networks. Given the popularity of LoRa it is likely that multiple independent LoRa networks are deployed in close proximity. In this situation, neighbouring networks interfere and methods have to be found to combat this interference. In this paper we investigate the use of directional antennae and the use of multiple base stations as methods of dealing with inter-network interference. Directional antennae increase signal strength at receivers without increasing transmission energy cost. Thus, the probability of successfully decoding the message in an interference situation is improved. Multiple base stations can alternatively be used to improve the probability of receiving a message in a noisy environment. We compare the effectiveness of these two approaches via simulation. Our findings show that both methods are able to improve LoRa network performance in interference settings. However, the results show that the use of multiple base stations clearly outperforms the use of directional antennae. For example, in a setting where data is collected from 600 nodes which are interfered by four networks with 600 nodes each, using three base stations improves the Data Extraction Rate (DER) from 0.24 to 0.56 while the use of directional antennae provides an increase to only 0.32.

cs.NI↗