Showing 1–50 of 61 results for author: Fitzek, F H P

Feynman Meets Turing: The Curse of Quantum Universality

Authors: Yannik N. Böck, Holger Boche, Frank H. P. Fitzek

Abstract: We consider a formal model of quantum circuit description languages (QCDLs) in which semantically meaningful programs correspond to computable unitary matrices. We show that any semantically universal QCDL -- that is, any QCDL able to describe all computable unitary matrices, which in turn form the set of matrices we can meaningfully represent on digital hardware -- cannot have a semi-decidable se… ▽ More We consider a formal model of quantum circuit description languages (QCDLs) in which semantically meaningful programs correspond to computable unitary matrices. We show that any semantically universal QCDL -- that is, any QCDL able to describe all computable unitary matrices, which in turn form the set of matrices we can meaningfully represent on digital hardware -- cannot have a semi-decidable set of semantically meaningful descriptions. In particular, no such language admits a compiler that reliably recognizes all valid program descriptions. This result stands in contrast to classical programming languages. While compilation in languages such as C or C++ may itself involve non-terminating computations, the set of semantically meaningful programs remains recursively enumerable, since successful compilation provides a witness of validity. The essential difference lies in the nature of the semantic domains: classical languages describe partial recursive functions, whereas QCDLs describe total unitary operators. Our analysis establishes a fundamental limitation of quantum circuit description languages and highlights a structural distinction between classical and quantum models of computation at the level of formal language theory. △ Less

Submitted 17 July, 2026; originally announced July 2026.

VaporISAC: Integrated Sensing and Communication via Molecular Signals

Authors: Sunasheer Bhattacharjee, Martín Schottlender, Pit Hofmann, Juan A. Cabrera, Frank H. P. Fitzek, Falko Dressler

Abstract: Conventional electromagnetic (EM)-based integrated sensing and communication (ISAC) systems degrade in cluttered, obstructed, and radio-frequency-hostile environments, while macroscopic molecular communication (MC) remains largely unexplored as an ISAC medium. This article introduces VaporISAC, a molecular ISAC framework in which chemical vapor pulses simultaneously convey information and probe th… ▽ More Conventional electromagnetic (EM)-based integrated sensing and communication (ISAC) systems degrade in cluttered, obstructed, and radio-frequency-hostile environments, while macroscopic molecular communication (MC) remains largely unexplored as an ISAC medium. This article introduces VaporISAC, a molecular ISAC framework in which chemical vapor pulses simultaneously convey information and probe the propagation environment, enabling a one signal, two outputs paradigm. The same received waveform is jointly processed to recover transmitted information and infer environmental properties such as airflow, turbulence, smoke, and chemical conditions. Rather than replacing conventional EM-based ISAC, VaporISAC complements existing approaches in chemically dynamic, infrastructure-limited, and EM-challenged environments. The sensing principles, system architecture, proof-of-concept demonstrations, emerging applications, and open research challenges of VaporISAC are presented, positioning it as a promising new paradigm for resilient communication and environmental sensing. △ Less

Submitted 17 July, 2026; originally announced July 2026.

Comments: 7 pages, 1 table, 5 figures. Submitted to IEEE Communications Magazine for review

Identification Codes and Post-Shannon Communication: Theory, Architectures, and Emerging Applications

Authors: Wafa Labidi, Kumar Nilesh, Johannes Rosenberger, Juan Cabrera, Holger Boche, Christian Deppe, Frank H. P. Fitzek, Marc Geitz

Abstract: Identification (ID) coding, introduced by Ahlswede and Dueck, extends Shannon's classical communication paradigm by replacing message reconstruction with hypothesis testing. Instead of decoding the transmitted message, the receiver only decides whether a particular message was sent. A fundamental result of ID theory is the double-exponential growth in the number of identifiable messages with respe… ▽ More Identification (ID) coding, introduced by Ahlswede and Dueck, extends Shannon's classical communication paradigm by replacing message reconstruction with hypothesis testing. Instead of decoding the transmitted message, the receiver only decides whether a particular message was sent. A fundamental result of ID theory is the double-exponential growth in the number of identifiable messages with respect to (w.r.t.) the blocklength. This scaling behavior enables fundamentally new communication architectures for large-scale distributed systems and forms a key building block of post-Shannon communication. While ID cannot replace classical communication in general, it is particularly well-suited for scenarios in which full message reconstruction is unnecessary, such as monitoring, alarming, and control systems. In this survey, we review the theoretical foundations of ID coding and discuss emerging communication architectures and application domains based on this paradigm. Particular emphasis is placed on practical use cases, including monitoring systems, special-purpose data storage, joint identification and sensing (JIDAS), semantic communications, mobile-network control systems and networked consensus testing systems. We further highlight recent system concepts, industrial perspectives, and implementation examples that illustrate how ID-based principles can be realized in practical communication systems. △ Less

Submitted 16 July, 2026; originally announced July 2026.

Evaluating Encoding Strategies for Closed-Loop Classification in Biological Neural Networks

Authors: Martin Schottlender, Veronika Volkova, Pengjie Zhou, Ruifeng Zheng, Frank H. P. Fitzek, Pit Hofmann

Abstract: Interfacing with Biological Neural Networks (BNNs) requires encoding information into stimulation patterns that can be effectively processed and that enable the underlying system to adapt. Nevertheless, the role of stimulation encoding remains poorly understood. In this work, we compare multiple encoding strategies, including rate-based, phase-based, burst-based, and time-to-first-spike temporal e… ▽ More Interfacing with Biological Neural Networks (BNNs) requires encoding information into stimulation patterns that can be effectively processed and that enable the underlying system to adapt. Nevertheless, the role of stimulation encoding remains poorly understood. In this work, we compare multiple encoding strategies, including rate-based, phase-based, burst-based, and time-to-first-spike temporal encodings, in a closed-loop neural classification task using cultured BNNs. We encode visual inputs as spatiotemporal stimulation patterns delivered via a Multi-Electrode Array (MEA) and evaluate classification performance for each encoding scheme. We find that burst-based temporal encoding yields the highest observed performance, achieving up to 95.6 % accuracy in a binary classification task, compared to substantially lower performance from rate- and phase-based approaches. We further show that performance is highly sensitive to the spatial distribution of stimulation, with suboptimal electrode selection significantly degrading accuracy. These findings indicate that effective interfacing with biological neural systems requires the joint optimization of temporal and spatial encoding strategies, and highlight temporal encoding as a key design dimension for bio-digital computing. △ Less

Submitted 15 July, 2026; originally announced July 2026.

Comments: 6 pages, 3 figures, Submitted to IEEE BioCAS 2026

Vehicle-to-Grid as a 5G Smart Grid Vertical: Non-Technical Barriers and Implications for Communication Networks

Authors: Shangqing Wang, Laura del Rio Carazo, Frank H. P. Fitzek

Abstract: Vehicle-to-Grid (V2G) and broader Vehicle-to-Everything (V2X) technologies are technically mature and widely demonstrated, yet large-scale deployment is constrained mainly by non-technical rather than communication or power-electronics limits. This paper targets the wireless communications community and frames V2G as a 5G-enabled smart grid vertical, linking business, governance, social, and infra… ▽ More Vehicle-to-Grid (V2G) and broader Vehicle-to-Everything (V2X) technologies are technically mature and widely demonstrated, yet large-scale deployment is constrained mainly by non-technical rather than communication or power-electronics limits. This paper targets the wireless communications community and frames V2G as a 5G-enabled smart grid vertical, linking business, governance, social, and infrastructure barriers to concrete communication-system requirements. Building on a PRISMA-guided systematic review of 974 V2G/V2X publications (2009-2025), and 162 implementation-critical studies, we adopt a four-domain framework of non-technical barriers: Business/Economic, Governance/Policy, Social, and Infrastructure/Ecosystem. Temporal and regional analyses show a shift from technical dominance to multidisciplinary integration after 2021. We translate these domains into communication requirements for V2G verticals, including fine-grained metering and settlement, protocol interoperability (e.g., ISO~15118, OCPP), privacy-by-design data governance, latency- and reliability-differentiated services, and edge-cloud partitioning for flexibility control. The results demonstrate that 5G design for V2G cannot be a purely technical optimization task and must integrate socio-technical constraints from the outset, suggesting research directions for sustainable, data-driven V2G communication architectures. △ Less

Submitted 1 July, 2026; originally announced July 2026.

Comments: In European Wireless (EW), Rimini, Italy, 2026

The Shared Prosperity Internet

Authors: Juan A. Cabrera, Pit Hofmann, Jonas Schulz, Frederic Benken, Hrjehor Mark, Giang T. Nguyen, Holger Boche, Frank H. P. Fitzek

Abstract: The Shared Prosperity Internet (SPI) is a network-computing architecture that makes the benefits of automation and Artificial Intelligence (AI) broadly accessible to the society. To ground its design, this paper maps the physical constraints of Shannon, Landauer, Turing, and Einstein to three design principles: trustworthiness, sustainability, and technological sovereignty, and maps them into thre… ▽ More The Shared Prosperity Internet (SPI) is a network-computing architecture that makes the benefits of automation and Artificial Intelligence (AI) broadly accessible to the society. To ground its design, this paper maps the physical constraints of Shannon, Landauer, Turing, and Einstein to three design principles: trustworthiness, sustainability, and technological sovereignty, and maps them into three technical pillars: i) post-Shannon, goal-oriented communication that transmits only what the task requires; ii) anticipatory decision-making ("negative latency") with confidence-bounded pre-action and correction; and iii) beyond-digital computing that selects energy-optimal substrates under deadline and computability constraints. The SPI is grounded in three societal use cases: remote teaching for pupils, remote teaching of robots and cyber-physical systems, and elder care. Furthermore, this paper defines measurable outcomes for an SPI, including latency decomposition, bits per event, energy and CO2 per task, safety and privacy indicators, and robustness. △ Less

Submitted 15 May, 2026; originally announced May 2026.

Comments: 8 pages, conference, 4 figures, 16 references

Enabling Intelligent Bidirectional Charging: A Real-World Communication Interface Between Electric Vehicles, Charging Infrastructure, and a Control Optimizer

Authors: Shangqing Wang, Abhirup Sain, Christopher Lehmann, Shiwei Shen, Razan Habeeb, Frank H. P. Fitzek

Abstract: This paper presents the real-world implementation and field validation of a user-aware bidirectional electric vehicle (EV) charging system developed within the Mobilities for EU and DymoBat projects in Dresden. Building on earlier simulation frameworks, the system enables transition from conceptual models to operational deployment in urban environments. To support grid flexibility and sustainabl… ▽ More This paper presents the real-world implementation and field validation of a user-aware bidirectional electric vehicle (EV) charging system developed within the Mobilities for EU and DymoBat projects in Dresden. Building on earlier simulation frameworks, the system enables transition from conceptual models to operational deployment in urban environments. To support grid flexibility and sustainable mobility, the solution combines real-time vehicle and user data with a centralized optimization platform to enable dynamic charging and discharging decisions. The architecture integrates a wireless On-Board Diagnostic II (OBD-II) interface and an open middleware node connected via a 5G campus network, allowing early access to vehicle state-of-charge before plug-in. A tablet-based interface captures user preferences such as departure time and energy demand, which are incorporated into the optimization together with grid conditions. A key contribution is a multi-level communication architecture linking the EV, charging station, user interface, and grid control center using the Open Charge Point Protocol (OCPP). The system integrates software, embedded hardware, and network communication for real-time charging management. Field deployment at Ostra Sport Park in Dresden demonstrates feasibility, improved load balancing, and robust vehicle-to-grid operation. The results show that early data acquisition and predictive control can enhance system efficiency. This work provides a practical benchmark for positive energy districts and future urban e-mobility systems. △ Less

Submitted 15 May, 2026; originally announced May 2026.

Journal ref: E-Mobility Power System Integration Symposium, 2025 In: E-Mobility Power System Integration Symposium, pp. 8, Berlin, Germany, 2025

Deterministic positioning of circular Bragg gratings using atomic force lithography for high-performance quantum dot light sources

Authors: Sai Abhishikth Dhurjati, Moritz Langer, Yared G. Zena, Ahmad Rahimi, Liesa Raith, Martin Bauer, Frank H. P. Fitzek, Riccardo Bassoli, Caspar Hopfmann

Abstract: Semiconductor quantum dots (QDs) grown by molecular beam epitaxy are excellent quantum emitters, but their random spatial distribution hinders deterministic coupling to optical microcavities. We demonstrate a room-temperature atomic force microscopy (AFM)-assisted nano-oxidation lithography technique enabling QD positioning with a radial displacement of $51(28)$ nm. Free-standing asymmetric circul… ▽ More Semiconductor quantum dots (QDs) grown by molecular beam epitaxy are excellent quantum emitters, but their random spatial distribution hinders deterministic coupling to optical microcavities. We demonstrate a room-temperature atomic force microscopy (AFM)-assisted nano-oxidation lithography technique enabling QD positioning with a radial displacement of $51(28)$ nm. Free-standing asymmetric circular Bragg gratings incorporating AFM-positioned GaAs QDs exhibit a $245$-fold photoluminescence enhancement and fine-structure splitting (FSS) comparable to bulk QDs. Polarization-resolved spectroscopy and finite-difference time-domain simulations show robust emission for displacements up to $50$ nm (Stokes parameter $\lvert S \rvert < 0.05$ ). The devices display stable FSS and polarization imbalance below $5 \, \%$ , confirming precise, reproducible alignment and potential for high fidelity devices. This scalable approach enables deterministic integration of high-performance QDs with photonic cavities, advancing practical quantum light sources for quantum information technologies. △ Less

Submitted 5 May, 2026; originally announced May 2026.

Comments: 21 pages, 9 figures

Free-standing circular Bragg gratings enabling efficient GaAs quantum dot entangled photon pair sources

Authors: Sai Abhishikth Dhurjati, Moritz Langer, Yared G. Zena, Ahmad Rahimi, Liesa Raith, Martin Bauer, Frank H. P. Fitzek, Riccardo Bassoli, Caspar Hopfmann

Abstract: Deterministic and bright quantum light sources based on scalable semiconductor technologies are a crucial building block for future quantum communication networks. While circular Bragg gratings (CBGs) are highly effective for extracting light from solid-state quantum emitters, conventional architectures rely on complex multi-layer processing or flip-chip bonding, which introduce detrimental strain… ▽ More Deterministic and bright quantum light sources based on scalable semiconductor technologies are a crucial building block for future quantum communication networks. While circular Bragg gratings (CBGs) are highly effective for extracting light from solid-state quantum emitters, conventional architectures rely on complex multi-layer processing or flip-chip bonding, which introduce detrimental strain and limit scalability. Here, we present a fabrication-minimal approach to realize monolithic, free-standing CBG cavities with deterministically positioned single GaAs quantum dots (QDs). By utilizing aspect-ratio-dependent etching (ARDE) in a single-step top-down process, we achieve the necessary vertical structural asymmetry for directional emission without requiring bottom reflectors. Finite-difference time-domain (FDTD) simulations validate this geometry, predicting free-space extraction efficiencies up to $68 \, \%$ and coupling efficiencies of $40 \, \%$ into a lensed single-mode fiber ($\text{NA} = 0.6$). Experimentally, the deterministically coupled QD-CBG devices yield a photoluminescence intensity enhancement of up to $\times 700$ compared to unprocessed planar QDs, reaching integrated count rates of $45 \, MHz$. Furthermore, the suspended membrane architecture effectively relaxes residual strain, significantly reducing the average exciton fine-structure splitting from $7.3 \, μeV$ in planar QDs to $1.3 \, μeV$ in the CBGs. Interferometric measurements confirm that the fabrication process preserves the optical quality of the emitters, with average coherence times of $70 \, ps$. By bridging optimized FDTD design with precise nanofabrication and robust optical performance, these results establish free-standing GaAs CBGs as a highly scalable platform for bright and coherent entangled photon pair sources. △ Less

Submitted 4 May, 2026; originally announced May 2026.

Comments: 19 pages, 9 figures

Molecular ISAC via Markov State-Space Modeling: Joint Distance Sensing and Data Detection

Authors: Ruifeng Zheng, Pengjie Zhou, Martín Schottlender, Veronika Volkova, Juan A. Cabrera, Frank H. P. Fitzek, Pit Hofmann

Abstract: This paper develops a molecular integrated sensing and communication (ISAC) framework that exploits the same molecular observations for physical-parameter sensing and data detection. As a representative instantiation, we consider a microfluidic molecular communication (MC) channel and study transmitter--receiver (TX--RX) distance sensing, where the distance affects the propagation delay, transient… ▽ More This paper develops a molecular integrated sensing and communication (ISAC) framework that exploits the same molecular observations for physical-parameter sensing and data detection. As a representative instantiation, we consider a microfluidic molecular communication (MC) channel and study transmitter--receiver (TX--RX) distance sensing, where the distance affects the propagation delay, transient response, and inter-symbol interference structure. A distance-parameterized Markov state--space model is established to obtain distance-dependent channel impulse responses and a block observation model for on-off keying signaling. Based on this model, we design a pilot-assisted low-complexity receiver that combines distance initialization, decision-feedback equalization (DFE), and iterative joint refinement. Numerical results show accurate distance sensing and improved bit error ratio (BER), demonstrating the mutual benefit between sensing and communication and highlighting microfluidic MC as a representative platform for molecular ISAC. △ Less

Submitted 3 May, 2026; originally announced May 2026.

Comments: 6 pages

Synthetic Biological Intelligence: System-Level Abstractions and Adaptive Bio-Digital Interaction

Authors: Martin Schottlender, Pengjie Zhou, Veronika Volkova, Fatima Rani, Ruifeng Zheng, Juan A. Cabrera, Frank H. P. Fitzek, Pit Hofmann

Abstract: Concurrent advances across fields such as organoid technology, Microelectrode Arrays (MEAs), neuromorphic computing, and machine learning have given rise to a groundbreaking research paradigm: Synthetic Biological Intelligence (SBI). SBI refers to engineered systems in which living Biological Neural Networks (BNNs) are interfaced with hardware and software to perform task-oriented information proc… ▽ More Concurrent advances across fields such as organoid technology, Microelectrode Arrays (MEAs), neuromorphic computing, and machine learning have given rise to a groundbreaking research paradigm: Synthetic Biological Intelligence (SBI). SBI refers to engineered systems in which living Biological Neural Networks (BNNs) are interfaced with hardware and software to perform task-oriented information processing in a closed loop. This cutting-edge technology, while still in its infancy, has the potential to deliver highly efficient performance across both computing capabilities and energy consumption. The early stage of this field underscores the need for reliable multi-scale and cross-domain interaction interfaces to support applications in robotics, biomedicine, signal processing, and neuroscience research. The hitherto lack of commercially available SBI platforms has slowed the development, as the conditions to produce a testbed are expensive and cumbersome. The introduction of standardized, platform- and cloud-integrated BNNs has been a crucial catalyst for the scientific community, improving the accessibility of SBI and leading the way to further developments. In this survey, we summarize the innovations that contributed to the emergence of SBI and the first testbed interfaces that enabled its embodiment. This work reframes SBI as a bio-digital interaction system and introduces a unified protocol across encoding, decoding, system engineering, and benchmarking. △ Less

Submitted 30 April, 2026; originally announced April 2026.

Comments: 27 pages, 6 figures

Compact system development of efficient quantum-entangled photon sources towards deployable and industrial devices

Authors: Yared G. Zena, Moritz Langer, Ahmad Rahimi, Abhishikth Dhurjati, Pavel Ruchka, Sara Jakovljevic, Mandira Pal, Frank H. P. Fitzek, Harald Giessen, Juergen Czarske, Riccardo Bassoli, Caspar Hopfmann

Abstract: Entangled photon pair sources are a key enabling technology for quantum communication and networking, yet their deployment beyond laboratory environments is hindered by system-level complexity, limited operational stability, and insufficient industry compatibility. Here, we demonstrate a rack-based, mobile quantum light source architecture based on a semiconductor quantum dot emitter that directly… ▽ More Entangled photon pair sources are a key enabling technology for quantum communication and networking, yet their deployment beyond laboratory environments is hindered by system-level complexity, limited operational stability, and insufficient industry compatibility. Here, we demonstrate a rack-based, mobile quantum light source architecture based on a semiconductor quantum dot emitter that directly addresses these challenges through modular system integration and automated operation. The source generates polarization-entangled photon pairs with an entanglement negativity 2n of up to $0.98(1)$, confirming near-maximal entanglement quality. In continuous, hands-off operation over a six-hour time window, the system achieves an average single-photon emission rate of $697(8)$ kHz and a maximum rate of $740(7)$ kHz, while maintaining 2n-value of more than $95$ $\%$. These results are enabled by the integration of optical excitation, collection, cryogenic operation, and control electronics within a standardized rack footprint, together with automated monitoring. By demonstrating simultaneously high entanglement quality, sustained brightness, and long-term operational stability in an industry-aligned system architecture, this work advances semiconductor quantum dot sources toward deployable entangled photon sources for applied quantum photonics. △ Less

Submitted 2 April, 2026; originally announced April 2026.

Comments: 22 Pages, 10 figures

Two-Qubit Implementation of QAOA for MAX-CUT on an NV-Center Quantum Processor

Authors: Leon E. Röscher, Talía L. M. Lezama, Luca Cimino, Jonah vom Hofe, Riccardo Bassoli, Frank H. P. Fitzek

Abstract: We report a proof-of-principle implementation of the quantum approximate optimization algorithm (QAOA) for the smallest nontrivial MAX-CUT instance on an NV-center-based quantum processor operating at room temperature. The two-qubit register is encoded in the electron spin and the ${}^{14}\mathrm{N}$ nuclear spin of a single NV$^-$ center. Using a minimization formulation of MAX-CUT, we implement… ▽ More We report a proof-of-principle implementation of the quantum approximate optimization algorithm (QAOA) for the smallest nontrivial MAX-CUT instance on an NV-center-based quantum processor operating at room temperature. The two-qubit register is encoded in the electron spin and the ${}^{14}\mathrm{N}$ nuclear spin of a single NV$^-$ center. Using a minimization formulation of MAX-CUT, we implement a single-layer QAOA ansatz with native entangling and single-qubit control operations. Because the optical readout of the NV$^-$ center is not projective in the computational basis, we reconstruct computational-basis populations from averaged fluorescence signals and use them to determine the experimental QAOA cost landscape by scanning the variational parameters. These results show that the core elements of QAOA can be realized on this platform and establish a baseline for future improvements in phase tracking, coherence-preserving control, and scaling to larger problem sizes. △ Less

Submitted 1 April, 2026; originally announced April 2026.

Markov State--Space Modeling and Channel Characterization for DNA-Based Molecular Communication

Authors: Ruifeng Zheng, Zhihan Xu, Veronika Volkova, Pengjie Zhou, Martín Schottlender, Juan A. Cabrera, Frank H. P. Fitzek, Pit Hofmann

Abstract: In this paper, we study DNA-based molecular communication with microarray-style reception under reversible hybridization, where the bound-state observation exhibits both inter-symbol interference and colored counting noise. To capture these effects in a communication-oriented form, we develop a Markov state-space framework based on a voxelized reaction--diffusion model, in which a block-structured… ▽ More In this paper, we study DNA-based molecular communication with microarray-style reception under reversible hybridization, where the bound-state observation exhibits both inter-symbol interference and colored counting noise. To capture these effects in a communication-oriented form, we develop a Markov state-space framework based on a voxelized reaction--diffusion model, in which a block-structured transition matrix describes molecular transport and binding/unbinding dynamics. For the microarray specialization, this representation yields the channel impulse response, the equilibrium gain, and a settling-time-based characterization of the effective channel memory. Building on the resulting symbol-rate observation model for on--off keying, we derive a grouped-binomial counting model and obtain a closed-form expression for the covariance of the counting noise. Based on these statistics, we further develop a differential-threshold detector and a finite-memory decision-feedback equalizer. Numerical results validate the theoretical correlation behavior and show that the relative performance of the proposed receivers depends strongly on the channel-memory regime. △ Less

Submitted 24 March, 2026; originally announced March 2026.

Comments: 13 pages

Fly-PRAC: Packet Recovery for Random Linear Network Coding

Authors: Hosein K. Nazari, Stefan Senk, Peyman Pahlevani, Juan A. Cabrera, Frank H. P. Fitzek

Abstract: Network Coding (NC) is a compelling solution for increasing network efficiency. However, it discards corrupted packets and cannot achieve optimal performance in noisy communications. Since most of the information in corrupted packets is error-free, discarding them is not the best strategy. Several packet recovery techniques such as PRAC and S-PRAC were proposed to exploit corrupted packets. Yet, t… ▽ More Network Coding (NC) is a compelling solution for increasing network efficiency. However, it discards corrupted packets and cannot achieve optimal performance in noisy communications. Since most of the information in corrupted packets is error-free, discarding them is not the best strategy. Several packet recovery techniques such as PRAC and S-PRAC were proposed to exploit corrupted packets. Yet, they are slow and only practical when the packet size is small and communication channels are not very noisy. We propose a packet recovery scheme called Fly-PRAC to address these issues. Fly-PRAC exploits algebraic relations between a group of coded packets to estimate their corrupted parts and recovers them. Unlike previous schemes, Fly-PRAC can recover coded packets at the intermediate node without decoding them. We have compared Fly-PRAC against S-PRAC. Results show when the bit error rate (ε) is 10^-4, Fly-PRAC outperforms S-PRAC by two folds for a payload of 900B. In two-hop communication with ε = 10^-4 and a payload size of 500B, by enabling the recovery in the intermediate node, Fly-PRAC reduces transmissions by 16%. In a Sparse Network Coding (SNC) scenario, with two non-zero elements in the coefficient vectors and a payload of 800B, there is a reduction by 31% on average for decoding delay. △ Less

Submitted 10 March, 2026; originally announced March 2026.

Modulation, ISI, and Detection for Langmuir Adsorption-Based Microfluidic Molecular Communication

Authors: Ruifeng Zheng, Pengjie Zhou, Pit Hofmann, Martín Schottlender, Fatima Rani, Juan A. Cabrera, Frank H. P. Fitzek

Abstract: This paper studies microfluidic molecular communication receivers with finite-capacity Langmuir adsorption driven by an effective surface concentration. In the reaction-limited regime, we derive a closed-form single-pulse response kernel and a symbol-rate recursion for on-off keying that explicitly exposes channel memory and inter-symbol interference. We further develop short-pulse and long-pulse… ▽ More This paper studies microfluidic molecular communication receivers with finite-capacity Langmuir adsorption driven by an effective surface concentration. In the reaction-limited regime, we derive a closed-form single-pulse response kernel and a symbol-rate recursion for on-off keying that explicitly exposes channel memory and inter-symbol interference. We further develop short-pulse and long-pulse approximations, revealing an interference asymmetry in the long-pulse regime due to saturation. To account for stochasticity, we adopt a finite-receptor binomial counting model, employ pulse-end sampling, and propose a low-complexity midpoint-threshold detector that reduces to a fixed threshold when interference is negligible. Numerical results corroborate the proposed characterization and quantify detection performance versus pulse and symbol durations. △ Less

Submitted 16 January, 2026; originally announced January 2026.

Comments: 5 pages

Closed-form Solution of Wahba's Problem for Pairwise Similar Quaternions

Authors: Hristina Radak, Christian Scheunert, Frank H. P. Fitzek

Abstract: Wahba's problem is fundamental to spacecraft attitude estimation, seeking the optimal rotation that minimizes the weighted misalignment between sets of vector observations. Traditional solvers, including Davenport's $q$-method, QUEST, and ESOQ, reformulate the problem as an eigenvalue task for a $4 \times 4$ symmetric matrix, a process that obscures the underlying algebraic structure of the soluti… ▽ More Wahba's problem is fundamental to spacecraft attitude estimation, seeking the optimal rotation that minimizes the weighted misalignment between sets of vector observations. Traditional solvers, including Davenport's $q$-method, QUEST, and ESOQ, reformulate the problem as an eigenvalue task for a $4 \times 4$ symmetric matrix, a process that obscures the underlying algebraic structure of the solution. This paper presents a novel, entirely quaternion-based closed-form solution for the pairwise similar quaternions. By establishing a direct connection to the homogeneous singular Sylvester equation: (i) we derive the necessary and sufficient condition for the existence of a quaternion that achieves zero Wahba's cost; (ii) we provide a closed-form analytic expression for the corresponding solution set; and (iii) we propose the computationally efficient and numerically stable Minimal Analytic Rotation Algorithm (MARA). Computational complexity analysis demonstrates that MARA achieves a $35.11\%$ reduction in total floating-point operations (FLOPs) compared to the state-of-the-art ESOQ2 algorithm. Numerical validation via $10^6$ Monte Carlo trials confirms that MARA achieves higher accuracy than established optimal solvers under stochastic noise, offering a computationally more efficient and analytically transparent alternative for high-frequency attitude determination systems. △ Less

Submitted 8 June, 2026; v1 submitted 8 December, 2025; originally announced December 2025.

Communicating Properties of Quantum States over Classical Noisy Channels

Authors: Nikhitha Nunavath, Jiechen Chen, Osvaldo Simeone, Riccardo Bassoli, Frank H. P. Fitzek

Abstract: Transmitting information about quantum states over classical noisy channels is an important problem with applications to science, computing, and sensing. This task, however, poses fundamental challenges due to the exponential scaling of state space with system size. We introduce shadow tomography-based transmission with unequal error protection (STT-UEP), a novel communication protocol that enable… ▽ More Transmitting information about quantum states over classical noisy channels is an important problem with applications to science, computing, and sensing. This task, however, poses fundamental challenges due to the exponential scaling of state space with system size. We introduce shadow tomography-based transmission with unequal error protection (STT-UEP), a novel communication protocol that enables efficient transmission of properties of quantum states, allowing decoder-side estimation of arbitrary local Pauli observables. Unlike conventional approaches requiring the transmission of a number of bits that is exponential in the number of qubits, STT-UEP achieves communication complexity that scales logarithmically with the number of observables, depending on the observable weight. The protocol exploits classical shadow tomography for measurement efficiency, and applies unequal error protection by encoding measurement bases with stronger channel codes than measurement outcomes. We provide theoretical guarantees on estimation accuracy as a function of the bit error probability of the classical channel, and validate the approach against several benchmarks via numerical results. △ Less

Submitted 1 June, 2026; v1 submitted 4 December, 2025; originally announced December 2025.

Comments: Published in IEEE Communications Letters

Temperature-dependent refractive index of AlGaAs for quantum-photonic devices near the bandgap

Authors: Moritz Langer, Sai Abhishikth Dhurjati, Martin Bauer, Yared Getahun Zena, Ahmad Rahimi, Riccardo Bassoli, Frank H. P. Fitzek, Oliver G. Schmidt, Caspar Hopfmann

Abstract: We present an experimental method to determine the refractive index of $Al_{x}Ga_{1-x}As$ (x = 0.0 - 0.5) from 300 K to 4 K across the 500 - 1100 nm wavelength range. The values are extracted from spectroscopically observed microcavity resonances in thin $Al_{x}Ga_{1-x}As$ membranes embedded between fully and partially reflective gold mirrors. Refined Varshni and Paessler models are used to descri… ▽ More We present an experimental method to determine the refractive index of $Al_{x}Ga_{1-x}As$ (x = 0.0 - 0.5) from 300 K to 4 K across the 500 - 1100 nm wavelength range. The values are extracted from spectroscopically observed microcavity resonances in thin $Al_{x}Ga_{1-x}As$ membranes embedded between fully and partially reflective gold mirrors. Refined Varshni and Paessler models are used to describe temperature-dependent bandgap shifts and material composition. By tracking resonance shifts and benchmarking against finite-difference time-domain simulations, we derive the dispersive optical response with high precision. This yields a quantitatively improved analytical expression for the refractive index of $Al_{x}Ga_{1-x}As$ matching the experimental results with a coefficient of determination as high as $R^2=0.993$, enabling accurate modeling near the band edge at cryogenic temperatures. The method is straightforward and broadly applicable to other semiconductor systems, offering a valuable tool for the design of micro photonic devices such as quantum light sources. △ Less

Submitted 1 December, 2025; originally announced December 2025.

Comments: 12 Pages, 9 figures

MSC Class: 78.67; 81.04

System Modeling of Microfluidic Molecular Communication: A Markov Approach

Authors: Ruifeng Zheng, Pengjie Zhou, Pit Hofmann, Fatima Rani, Juan A. Cabrera, Frank H. P. Fitzek

Abstract: This paper presents a Markov-based system model for microfluidic molecular communication (MC) channels. By discretizing the advection-diffusion dynamics, the proposed model establishes a physically consistent state-space formulation. The transition matrix explicitly captures diffusion, advective flow, reversible binding, and flow-out effects. The resulting discrete-time formulation enables analyti… ▽ More This paper presents a Markov-based system model for microfluidic molecular communication (MC) channels. By discretizing the advection-diffusion dynamics, the proposed model establishes a physically consistent state-space formulation. The transition matrix explicitly captures diffusion, advective flow, reversible binding, and flow-out effects. The resulting discrete-time formulation enables analytical characterization of both transient and equilibrium responses through a linear system representation. Numerical results verify that the proposed framework accurately reproduces channel behaviors across a wide range of flow conditions, providing a tractable basis for the design and analysis of MC systems in microfluidic environments. △ Less

Submitted 10 November, 2025; originally announced November 2025.

Comments: 6 pages, 5 figures. Submitted to IEEE International Conference on Communications (ICC) 2026

On solutions of singular Sylvester equations in quaternions

Authors: Hristina Radak, Christian Scheunert, Frank H. P. Fitzek

Abstract: The quaternionic equations ax-xb=0 and ax-xb=c are investigated, which are called homogeneous and inhomogeneous Sylvester equations, respectively. Conditions for the existence of solutions are provided. In addition, the general and nonzero solutions to these equations are derived applying quaternion square roots. The quaternionic equations ax-xb=0 and ax-xb=c are investigated, which are called homogeneous and inhomogeneous Sylvester equations, respectively. Conditions for the existence of solutions are provided. In addition, the general and nonzero solutions to these equations are derived applying quaternion square roots. △ Less

Submitted 5 June, 2026; v1 submitted 6 October, 2025; originally announced October 2025.

Communicating Smartly in Molecular Communication Environments: Neural Networks in the Internet of Bio-Nano Things

Authors: Jorge Torres Gómez, Pit Hofmann, Lisa Y. Debus, Osman Tugay Başaran, Sebastian Lotter, Roya Khanzadeh, Stefan Angerbauer, Bige Deniz Unluturk, Sergi Abadal, Werner Haselmayr, Frank H. P. Fitzek, Robert Schober, Falko Dressler

Abstract: Recent developments in the Internet of Bio-Nano-Things (IoBNT) are laying the foundation for innovative healthcare applications that envision a network of remotely coordinated nanodevices within the human body to monitor and actuate over potential diseases. However, interconnecting such nanodevices requires communication strategies that can cope with molecular communication (MC) channels, whose co… ▽ More Recent developments in the Internet of Bio-Nano-Things (IoBNT) are laying the foundation for innovative healthcare applications that envision a network of remotely coordinated nanodevices within the human body to monitor and actuate over potential diseases. However, interconnecting such nanodevices requires communication strategies that can cope with molecular communication (MC) channels, whose complex, stochastic, and dynamic behavior often makes accurate physical modeling infeasible. To explore the limits of nanodevice interconnectivity under these conditions, this survey focuses on data-driven communication strategies for MC systems, with particular emphasis on machine learning (ML) methods and neural network (NN) architectures for a robust and adaptive communication scheme at the nanoscale. Research on NN-enabled MC spans several aspects covered in this survey, including NNs for communication in IoBNT networks, the feasibility of biocompatible NN realization, explainable approaches, and the generation of training datasets. We also include open-source code examples to support reproducible research across key MC scenarios. Finally, we identify emerging challenges, including the need for robust NN architectures, biologically integrated NN modules, and scalable training strategies. △ Less

Submitted 31 May, 2026; v1 submitted 25 June, 2025; originally announced June 2025.

Comments: Published at IEEE Communications Surveys & Tutorials

Quantum Enhanced Entropy Pool for Cryptographic Applications and Proofs

Authors: Buniechukwu Njoku, Sonai Biswas, Milad Ghadimi, Mohammad Shojafar, Gabriele Gradoni, Riccardo Bassoli, Frank H. P. Fitzek

Abstract: This paper investigates the integration of quantum randomness into Verifiable Random Functions (VRFs) using the Ed25519 elliptic curve to strengthen cryptographic security. By replacing traditional pseudorandom number generators with quantum entropy sources, we assess the impact on key security and performance metrics, including execution time, and resource usage. Our approach simulates a modified… ▽ More This paper investigates the integration of quantum randomness into Verifiable Random Functions (VRFs) using the Ed25519 elliptic curve to strengthen cryptographic security. By replacing traditional pseudorandom number generators with quantum entropy sources, we assess the impact on key security and performance metrics, including execution time, and resource usage. Our approach simulates a modified VRF setup where initialization keys are derived from a quantum random number generator source (QRNG). The results show that while QRNGs could enhance the unpredictability and verifiability of VRFs, their incorporation introduces challenges related to temporal and computational overhead. This study provides valuable insights into the trade-offs of leveraging quantum randomness in API-driven cryptographic systems and offers a potential path toward more secure and efficient protocol design. The QRNG-based system shows increased (key generation times from 50 to 400+ microseconds, verification times from 500 to 3500 microseconds) and higher CPU usage (17% to 30%) compared to the more consistent performance of a Go-based VRF (key generation times below 200 microseconds, verification times under 2000 microseconds, CPU usage below 10%), highlighting trade-offs in computational efficiency and resource demands. △ Less

Submitted 17 June, 2025; originally announced June 2025.

Comments: 6 pages, 6 figures, Conference: IEEE Future Networks World Forum 2024

Towards a Base-Station-on-Chip: RISC-V Hardware Acceleration for wireless communication

Authors: Javier Acevedo, Frank H. P. Fitzek

Abstract: The evolution of 5G and the emergence of 6G wireless communication systems impose higher demands for computing capabilities and lower power consumption in the front-end and processing circuitry. Furthermore, the incorporation of Artificial Intelligence (AI)/Machine Learning (ML) in the Radio Access Network (RAN) introduces heightened computational needs and stringent low-latency requirements for b… ▽ More The evolution of 5G and the emergence of 6G wireless communication systems impose higher demands for computing capabilities and lower power consumption in the front-end and processing circuitry. Furthermore, the incorporation of Artificial Intelligence (AI)/Machine Learning (ML) in the Radio Access Network (RAN) introduces heightened computational needs and stringent low-latency requirements for both training and inference. The concept of a Base Station on Chip (BSoC) addresses those demands by consolidating of the signal processing, neural network computations and network management functions into a single chip. This new computing platform relies on a sophisticated hardware/software co-design to optimize performance, power efficiency, and scalability, enabling a compact, yet adaptable and intelligent base station solution for next-generation wireless networks. This research investigates the efficient implementation of conventional Channel Estimation (CE), massive Multiple Input Multiple Output (mMIMO), and beamforming kernels on a state-of-the-art RISC-V vector Digital Signal Processors (DSP) to capitalize on Data Level Parallelism (DLP). Moreover, it explores how RISC-V Vector Extensions (RVV) combined with custom instructions can effectively address the throughput and latency demands of LOW Physical Layer (PHY) kernels. △ Less

Submitted 9 June, 2025; originally announced June 2025.

Comments: RISC-V Summit Europe, Paris, 12-15th May 2025

Continuously Ordered Hierarchies of Algorithmic Information in Digital Twinning and Signal Processing

Authors: Yannik N. Böck, Holger Boche, Frank H. P. Fitzek

Abstract: We consider a fractional-calculus example of a continuous hierarchy of algorithmic information in the context of its potential applications in digital twinning. Digital twinning refers to different emerging methodologies in control engineering that involve the creation of a digital replica of some physical entity. From the perspective of computability theory, the problem of ensuring the digital tw… ▽ More We consider a fractional-calculus example of a continuous hierarchy of algorithmic information in the context of its potential applications in digital twinning. Digital twinning refers to different emerging methodologies in control engineering that involve the creation of a digital replica of some physical entity. From the perspective of computability theory, the problem of ensuring the digital twin's integrity -- i.e., keeping it in a state where it matches its physical counterpart -- entails a notion of algorithmic information that determines which of the physical system's properties we can reliably deduce by algorithmically analyzing its digital twin. The present work investigates the fractional calculus of periodic functions -- particularly, we consider the Wiener algebra -- as an exemplary application of the algorithmic-information concept. We establish a continuously ordered hierarchy of algorithmic information among spaces of periodic functions -- depending on their fractional degree of smoothness -- in which the ordering relation determines whether a certain representation of some function contains ``more'' or ``less'' information than another. Additionally, we establish an analogous hierarchy among lp-spaces, which form a cornerstone of (traditional) digital signal processing. Notably, both hierarchies are (mathematically) ``dual'' to each other. From a practical perspective, our approach ultimately falls into the category of formal verification and (general) formal methods. △ Less

Submitted 3 May, 2025; originally announced May 2025.

Exhaled Breath Analysis Through the Lens of Molecular Communication: A Survey

Authors: Sunasheer Bhattacharjee, Dadi Bi, Pit Hofmann, Alexander Wietfeld, Sophie Becke, Michael Lommel, Pengjie Zhou, Ruifeng Zheng, Ulrich Kertzscher, Yansha Deng, Wolfgang Kellerer, Frank H. P. Fitzek, Falko Dressler

Abstract: Molecular Communication (MC) has long been envisioned to enable an Internet of Bio-Nano Things (IoBNT) with medical applications, where nanomachines within the human body conduct monitoring, diagnosis, and therapy at micro- and nanoscale levels. MC involves information transfer via molecules and is supported by well-established theoretical models. However, practically achieving reliable, energy-ef… ▽ More Molecular Communication (MC) has long been envisioned to enable an Internet of Bio-Nano Things (IoBNT) with medical applications, where nanomachines within the human body conduct monitoring, diagnosis, and therapy at micro- and nanoscale levels. MC involves information transfer via molecules and is supported by well-established theoretical models. However, practically achieving reliable, energy-efficient, and bio-compatible communication at these scales still remains a challenge. Air-Based Molecular Communication (ABMC) is a type of MC that operates over larger, meter-scale distances and extends even outside the human body. Therefore, devices and techniques to realize ABMC are readily accessible, and associated use cases can be very promising in the near future. Exhaled breath analysis has previously been proposed. It provides a non-invasive approach for health monitoring, leveraging existing commercial sensor technologies and reducing deployment barriers. The breath contains a diverse range of molecules and particles that serve as biomarkers linked to various physiological and pathological conditions. The plethora of proven methods, models, and optimization approaches in MC enable macroscale breath analysis, treating human as the transmitter, the breath as the information carrier, and macroscale sensors as the receiver. Using ABMC to interface with the inherent dynamic networks of cells, tissues, and organs could create a novel Internet of Bio Things (IoBT), a preliminary macroscale stage of the IoBNT. This survey extensively reviews exhaled breath modeling and analysis through the lens of MC, offering insights into theoretical frameworks and practical implementations from ABMC, bringing the IoBT a step closer to real-world use. △ Less

Submitted 25 April, 2025; originally announced April 2025.

Comments: 27 pages, 2 tables, 12 figures. Submitted to IEEE Communications Surveys & Tutorials for review

The Security of Quantum Computing in 6G: from Technical Perspectives to Ethical Implications

Authors: Luca Barbieri, Abdelkrim Menina, Riccardo Bassoli, Frank H. P. Fitzek

Abstract: Quantum technologies hold promise as essential components for the upcoming deployment of the future 6G network. In this future network, the security and trustworthiness requirements are not considered fulfilled with the current state of the quantum computers, as the malicious behaviour on the part of the service provider towards the user may still be present. Therefore, this article provides an in… ▽ More Quantum technologies hold promise as essential components for the upcoming deployment of the future 6G network. In this future network, the security and trustworthiness requirements are not considered fulfilled with the current state of the quantum computers, as the malicious behaviour on the part of the service provider towards the user may still be present. Therefore, this article provides an initial interdisciplinary work of regulations and solutions in the scope of trustworthy quantum computing for future 6G that can be viewed as complimentary regulations to the existing strategies shared by different actors of states and organizations. More precisely, we describe the importance of a reliable quantum service provider and its implication on the ethical aspects concerning digital sovereignty. By exploring the critical relationship between trustworthiness and digital sovereignty in the context of future 6G networks, we analyse a trade-off between accessibility to this new technology and preservation of digital sovereignty engaging in parallel the United Nation's (UN's) sustainable development goals. Furthermore, we propose a partnership model based on cooperation, coordination, and collaboration giving rise to a trusted, ethical, and inclusive quantum ecosystem, whose implications can spill over to the entire global scenario. △ Less

Submitted 14 April, 2025; originally announced April 2025.

Comments: This paper contains 9 pages and 3 figures

Bright quantum dot light sources using monolithic microlenses on gold back-reflectors

Authors: Moritz Langer, Sai A. Dhurjati, Yared G. Zena, Ahmad Rahimi, Mandira Pal, Liesa Raith, Sandra Nestler, Riccardo Bassoli, Frank H. P. Fitzek, Oliver G. Schmidt, Caspar Hopfmann

Abstract: We present the fabrication process of bright $GaAs$ quantum dot (QD) photon sources by non-deterministic embedding into broadband monolithic $Al_{0.15}Ga_{0.85}As$ microlens arrays on gold-coated substrates. Arrays of cylindrical photoresist templates, with diameters ranging from $2$ $μm$ to $5$ $μm$, are thermally reflowed and subsequently transferred into the $Al_{0.15}Ga_{0.85}As$ thin-film sem… ▽ More We present the fabrication process of bright $GaAs$ quantum dot (QD) photon sources by non-deterministic embedding into broadband monolithic $Al_{0.15}Ga_{0.85}As$ microlens arrays on gold-coated substrates. Arrays of cylindrical photoresist templates, with diameters ranging from $2$ $μm$ to $5$ $μm$, are thermally reflowed and subsequently transferred into the $Al_{0.15}Ga_{0.85}As$ thin-film semiconductor heterostructure with embedded quantum dots through an optimized anisotropic and three-dimensional shape-preserving reactive ion etching process. This methodology facilitated the fabrication of large-scale ($2$ $mm$ $\times$ $4$ $mm$) and densely packed arrays of uniformly shaped microlenses ($\sim$ $40 \times 10^3$ $mm^{-1}$), with the brightest emissions from QDs embedded in microlenses exhibiting lateral diameters and heights of $2.7$ $μm$ and $1.35$ $μm$, respectively. Finite-difference time-domain simulations of both idealized and fabricated lens shapes provide a comprehensive three-dimensional analysis of the device performance and optimization potentials such as anti-reflection coatings. It is found that free-space extraction (fiber-coupled) efficiencies of up to $62$ $\%$ ($37$ $\%$) are achievable for hemispherical QD-microlenses on gold-coated substrates. A statistical model for the fabrication yield of QD-microlenses is developed and experimentally corroborated by photoluminescence spectroscopy of fabricated microlens arrays. This analysis exhibited a free-space intensity enhancement by factors of up to $\times 200$ in approximately $1$ out of $200$ microlenses, showing good agreement to the theoretical expectations. This scalable fabrication strategy underscores the potential of these compact, high-efficiency sources offering new prospects for applications of these devices in future large-scale quantum networks. △ Less

Submitted 10 March, 2025; originally announced March 2025.

An ultra-compact deterministic source of maximally entangled photon pairs

Authors: M. Langer, P. Ruchka, A. Rahimi, S. Jakovljevic, Y. G. Zena, A. Danilov, M. Pal, R. Bassoli, F. H. P. Fitzek, O. G. Schmidt, H. Giessen, C. Hopfmann

Abstract: We present an ultra-compact source of maximally entangled on-demand photon pairs. Our results are based on coupling of single GaAs quantum dots that are embedded in monolithic micro-lenses to a single-mode fiber with directly attached to 3D-printed micro-optics (NA of 0.6) inside a cryogenic environment. This approach, which is geared towards future integration into industrial environments, yields… ▽ More We present an ultra-compact source of maximally entangled on-demand photon pairs. Our results are based on coupling of single GaAs quantum dots that are embedded in monolithic micro-lenses to a single-mode fiber with directly attached to 3D-printed micro-optics (NA of 0.6) inside a cryogenic environment. This approach, which is geared towards future integration into industrial environments, yields state-of-the-art entangled photon pair creation performance while retaining flexibility and adjustability required for long-term operation of such a device - all while dramatically reducing the overall system footprint. We demonstrate near diffraction-limited performance and hyperspectral imaging utilizing a 3D-printed micro-objective with a full width at half maximum resolution limit of 604(16) nm when operating the system at a cryogenic temperature of 3.8 K. Furthermore, we prove that this system can be used to achieve single photon emission rates of 392(20) kHz at a 76 MHz pump rate and purities of 99.2(5) % using two-photon resonant excitation. Utilizing the exciton-biexciton emission cascade available in GaAs quantum dots under resonant excitation, near maximally entangled photon pairs with peak entanglement negatives 2n of 0.96(2) in a 4 ps time window, and 0.81(1) when averaged over one exciton lifetime, are demonstrated. △ Less

Submitted 11 March, 2025; v1 submitted 17 February, 2025; originally announced February 2025.

Comments: 14 pages, 13 figures

Bidirectional Charging Use Cases: Innovations in E-Mobility and Power-Grid Flexibility

Authors: Shangqing Wang, Juan A. Cabrera, Frank H. P. Fitzek

Abstract: This paper explores the potential of Vehicle-to-Everything (V2X) technology to enhance grid stability and support sustainable mobility in Dresden's Ostra district. By enabling electric vehicles to serve as mobile energy storage units, V2X offers grid stabilization and new business opportunities. We examine pilot projects and business use cases, focusing on Building Integrated Vehicle Energy Soluti… ▽ More This paper explores the potential of Vehicle-to-Everything (V2X) technology to enhance grid stability and support sustainable mobility in Dresden's Ostra district. By enabling electric vehicles to serve as mobile energy storage units, V2X offers grid stabilization and new business opportunities. We examine pilot projects and business use cases, focusing on Building Integrated Vehicle Energy Solutions (BIVES) and Resilient Energy Storage and Backup (RESB) as stepping stones towards full Vehicle-to-Grid (V2G) implementation. Our analysis highlights the feasibility, advantages, and challenges of implementing V2X in urban settings, underscoring its significant role in transitioning to a resilient, low-carbon urban energy system. The paper concludes with recommendations for addressing technical, regulatory, and business model challenges to accelerate V2X adoption in Dresden and beyond. △ Less

Submitted 5 December, 2024; originally announced December 2024.

Comments: 6 pages

Enabling Sustainable Urban Mobility: The Role of 5G Communication in the Mobilities for EU Project

Authors: Shangqing Wang, Christopher Lehmann, Rico Radeke, Frank H. P. Fitzek

Abstract: This paper examines the role of 5G communication in the Mobilities for EU project, a collaborative initiative involving 29 partners and 11 pilots aimed at revolutionizing urban mobility through electrification, automation, and connectivity. Focusing on Dresden as a Lead City, we explore the integration of 27 innovative solutions, including autonomous freight transport, eBuses, and charging robots,… ▽ More This paper examines the role of 5G communication in the Mobilities for EU project, a collaborative initiative involving 29 partners and 11 pilots aimed at revolutionizing urban mobility through electrification, automation, and connectivity. Focusing on Dresden as a Lead City, we explore the integration of 27 innovative solutions, including autonomous freight transport, eBuses, and charging robots, using a 5G communication network as the central framework. We analyze how 5G enables seamless connectivity and real-time data processing across diverse technologies, fostering interdependencies and synergies. This approach not only provides a cohesive understanding of the project's scope but also demonstrates 5G's critical role in smart city infrastructure. We evaluate the anticipated impact on sustainability metrics such as air quality, noise levels, CO2 emissions, and traffic congestion. The paper concludes by discussing challenges and strategies in leveraging 5G for comprehensive urban mobility solutions and its potential impact on future smart city developments. △ Less

Submitted 5 December, 2024; originally announced December 2024.

Comments: 6 pages

Advanced Plaque Modeling for Atherosclerosis Detection Using Molecular Communication

Authors: Alexander Wietfeld, Pit Hofmann, Jonas Fuchtmann, Pengjie Zhou, Ruifeng Zheng, Juan A. Cabrera, Frank H. P. Fitzek, Wolfgang Kellerer

Abstract: As one of the most prevalent diseases worldwide, plaque formation in human arteries, known as atherosclerosis, is the focus of many research efforts. Previously, molecular communication (MC) models have been proposed to capture and analyze the natural processes inside the human body and to support the development of diagnosis and treatment methods. In the future, synthetic MC networks are envision… ▽ More As one of the most prevalent diseases worldwide, plaque formation in human arteries, known as atherosclerosis, is the focus of many research efforts. Previously, molecular communication (MC) models have been proposed to capture and analyze the natural processes inside the human body and to support the development of diagnosis and treatment methods. In the future, synthetic MC networks are envisioned to span the human body as part of the Internet of Bio-Nano Things (IoBNT), turning blood vessels into physical communication channels. By observing and characterizing changes in these channels, MC networks could play an active role in detecting diseases like atherosclerosis. In this paper, building on previous preliminary work for simulating an MC scenario in a plaque-obstructed blood vessel, we evaluate different analytical models for non-Newtonian flow and derive associated channel impulse responses (CIRs). Additionally, we add the crucial factor of flow pulsatility to our simulation model and investigate the effect of the systole-diastole cycle on the received particles across the plaque channel. We observe a significant influence of the plaque on the channel in terms of the flow profile and CIR across different emission times in the cycle. These metrics could act as crucial indicators for early non-invasive plaque detection in advanced future MC methods. △ Less

Submitted 20 November, 2024; originally announced November 2024.

Comments: 6 pages, 6 figures

An Efficient Error Estimation Method in Quantum Key Distribution

Authors: Yingjian Wang, Yilun Hai, Buniechukwu Njoku, Koteswararao Kondepu, Riccardo Bassoli, Frank H. P. Fitzek

Abstract: Error estimation is an important step for error correction in quantum key distribution. Traditional error estimation methods require sacrificing a part of the sifted key, forcing a trade-off between the accuracy of error estimation and the size of the partial sifted key to be used and discarded. In this paper, we propose a hybrid approach that aims to preserve the entire sifted key after error est… ▽ More Error estimation is an important step for error correction in quantum key distribution. Traditional error estimation methods require sacrificing a part of the sifted key, forcing a trade-off between the accuracy of error estimation and the size of the partial sifted key to be used and discarded. In this paper, we propose a hybrid approach that aims to preserve the entire sifted key after error estimation while preventing Eve from gaining any advantage. The entire sifted key, modified and extended by our proposed method, is sent for error estimation in a public channel. Although accessible to an eavesdropper, the modified and extended sifted key ensures that the number of attempts to crack it remains the same as when no information is leaked. The entire sifted key is preserved for subsequent procedures, indicating the efficient utilization of quantum resources. △ Less

Submitted 11 November, 2024; originally announced November 2024.

Measurement Study of Programmable Network Coding in Cloud-native 5G and Beyond Networks

Authors: Osel Lhamo, Tung V. Doan, Elif Tasdemir, Mahdi Attawna, Giang T. Nguyen, Patrick Seeling, Martin Reisslein, Frank H. P. Fitzek

Abstract: Emerging 5G/6G use cases span various industries, necessitating flexible solutions that leverage emerging technologies to meet diverse and stringent application requirements under changing network conditions. The standard 5G RAN solution, retransmission, reduces packet loss but can increase transmission delay in the process. Random Linear Network Coding (RLNC) offers an alternative by proactively… ▽ More Emerging 5G/6G use cases span various industries, necessitating flexible solutions that leverage emerging technologies to meet diverse and stringent application requirements under changing network conditions. The standard 5G RAN solution, retransmission, reduces packet loss but can increase transmission delay in the process. Random Linear Network Coding (RLNC) offers an alternative by proactively sending combinations of original packets, thus reducing both delay and packet loss. Current research often only simulates the integration of RLNC in 5G while we implement and evaluate our approach on real commercially available hardware in a real-world deployment. We introduce Flexible Network Coding (FlexNC), which enables the flexible fusion of several RLNC protocols by incorporating a forwarder with multiple RLNC nodes. Network operators can configure FlexNC based on network conditions and application requirements. To further boost network programmability, our Recoder in the Network (RecNet) leverages intermediate network nodes to join the coding process. Both the proposed algorithms have been implemented on OpenAirInterface and extensively tested with traffic from different applications in a real network. While FlexNC adapts to various application needs of latency and packet loss, RecNet significantly minimizes packet loss for a remote user with minimal increase in delay compared to pure RLNC. △ Less

Submitted 12 August, 2024; originally announced August 2024.

Deep Reinforcement Learning for the Joint Control of Traffic Light Signaling and Vehicle Speed Advice

Authors: Johannes V. S. Busch, Robert Voelckner, Peter Sossalla, Christian L. Vielhaus, Roberto Calandra, Frank H. P. Fitzek

Abstract: Traffic congestion in dense urban centers presents an economical and environmental burden. In recent years, the availability of vehicle-to-anything communication allows for the transmission of detailed vehicle states to the infrastructure that can be used for intelligent traffic light control. The other way around, the infrastructure can provide vehicles with advice on driving behavior, such as ap… ▽ More Traffic congestion in dense urban centers presents an economical and environmental burden. In recent years, the availability of vehicle-to-anything communication allows for the transmission of detailed vehicle states to the infrastructure that can be used for intelligent traffic light control. The other way around, the infrastructure can provide vehicles with advice on driving behavior, such as appropriate velocities, which can improve the efficacy of the traffic system. Several research works applied deep reinforcement learning to either traffic light control or vehicle speed advice. In this work, we propose a first attempt to jointly learn the control of both. We show this to improve the efficacy of traffic systems. In our experiments, the joint control approach reduces average vehicle trip delays, w.r.t. controlling only traffic lights, in eight out of eleven benchmark scenarios. Analyzing the qualitative behavior of the vehicle speed advice policy, we observe that this is achieved by smoothing out the velocity profile of vehicles nearby a traffic light. Learning joint control of traffic signaling and speed advice in the real world could help to reduce congestion and mitigate the economical and environmental repercussions of today's traffic systems. △ Less

Submitted 18 September, 2023; originally announced September 2023.

Comments: 6 pages, 2 figures, accepted for publication at IEEE ICMLA 2023

An Overview of the NET Playground -- A Heterogeneous, Multi-Functional Network Test Bed

Authors: Paul Schwenteck, Sandra Zimmermann, Caspar von Lengerke, Giang T. Nguyen, Christian Scheunert, Frank H. P. Fitzek

Abstract: This paper provides an overview of the hardware and software components used in our test bed project the NET Playground. All source information is stored in the GitLab repository (https://gitlab.com/Paulteck/net-playground). In the Hardware section, we present sketches and 3D views of mechanical parts and technical drawings of printed boards. The Software section discusses relay control using shel… ▽ More This paper provides an overview of the hardware and software components used in our test bed project the NET Playground. All source information is stored in the GitLab repository (https://gitlab.com/Paulteck/net-playground). In the Hardware section, we present sketches and 3D views of mechanical parts and technical drawings of printed boards. The Software section discusses relay control using shell scripts and the utilization of Ansible for automation. We also introduce a C++ framework for connecting with the INA231 energy sensor. This paper serves as a reference for understanding and replicating our project's hardware and software components. △ Less

Submitted 5 July, 2023; originally announced July 2023.

Fast IMU-based Dual Estimation of Human Motion and Kinematic Parameters via Progressive In-Network Computing

Authors: Xiaobing Dai, Huanzhuo Wu, Siyi Wang, Junjie Jiao, Giang T. Nguyen, Frank H. P. Fitzek, Sandra Hirche

Abstract: Many applications involve humans in the loop, where continuous and accurate human motion monitoring provides valuable information for safe and intuitive human-machine interaction. Portable devices such as inertial measurement units (IMUs) are applicable to monitor human motions, while in practice often limited computational power is available locally. The human motion in task space coordinates req… ▽ More Many applications involve humans in the loop, where continuous and accurate human motion monitoring provides valuable information for safe and intuitive human-machine interaction. Portable devices such as inertial measurement units (IMUs) are applicable to monitor human motions, while in practice often limited computational power is available locally. The human motion in task space coordinates requires not only the human joint motion but also the nonlinear coordinate transformation depending on the parameters such as human limb length. In most applications, measuring these kinematics parameters for each individual requires undesirably high effort. Therefore, it is desirable to estimate both, the human motion and kinematic parameters from IMUs. In this work, we propose a novel computational framework for dual estimation in real-time exploiting in-network computational resources. We adopt the concept of field Kalman filtering, where the dual estimation problem is decomposed into a fast state estimation process and a computationally expensive parameter estimation process. In order to further accelerate the convergence, the parameter estimation is progressively computed on multiple networked computational nodes. The superiority of our proposed method is demonstrated by a simulation of a human arm, where the estimation accuracy is shown to converge faster than with conventional approaches. △ Less

Submitted 11 April, 2023; originally announced April 2023.

Machine Learning for QoS Prediction in Vehicular Communication: Challenges and Solution Approaches

Authors: Alexandros Palaios, Christian L. Vielhaus, Daniel F. Külzer, Cara Watermann, Rodrigo Hernangomez, Sanket Partani, Philipp Geuer, Anton Krause, Raja Sattiraju, Martin Kasparick, Gerhard Fettweis, Frank H. P. Fitzek, Hans D. Schotten, Slawomir Stanczak

Abstract: As cellular networks evolve towards the 6th generation, machine learning is seen as a key enabling technology to improve the capabilities of the network. Machine learning provides a methodology for predictive systems, which can make networks become proactive. This proactive behavior of the network can be leveraged to sustain, for example, a specific quality of service requirement. With predictive… ▽ More As cellular networks evolve towards the 6th generation, machine learning is seen as a key enabling technology to improve the capabilities of the network. Machine learning provides a methodology for predictive systems, which can make networks become proactive. This proactive behavior of the network can be leveraged to sustain, for example, a specific quality of service requirement. With predictive quality of service, a wide variety of new use cases, both safety- and entertainment-related, are emerging, especially in the automotive sector. Therefore, in this work, we consider maximum throughput prediction enhancing, for example, streaming or high-definition mapping applications. We discuss the entire machine learning workflow highlighting less regarded aspects such as the detailed sampling procedures, the in-depth analysis of the dataset characteristics, the effects of splits in the provided results, and the data availability. Reliable machine learning models need to face a lot of challenges during their lifecycle. We highlight how confidence can be built on machine learning technologies by better understanding the underlying characteristics of the collected data. We discuss feature engineering and the effects of different splits for the training processes, showcasing that random splits might overestimate performance by more than twofold. Moreover, we investigate diverse sets of input features, where network information proved to be most effective, cutting the error by half. Part of our contribution is the validation of multiple machine learning models within diverse scenarios. We also use explainable AI to show that machine learning can learn underlying principles of wireless networks without being explicitly programmed. Our data is collected from a deployed network that was under full control of the measurement team and covered different vehicular scenarios and radio environments. △ Less

Submitted 22 August, 2023; v1 submitted 23 February, 2023; originally announced February 2023.

Comments: 18 pages, 12 Figures. Accepted on IEEE Access

Berlin V2X: A Machine Learning Dataset from Multiple Vehicles and Radio Access Technologies

Authors: Rodrigo Hernangómez, Philipp Geuer, Alexandros Palaios, Daniel Schäufele, Cara Watermann, Khawla Taleb-Bouhemadi, Mohammad Parvini, Anton Krause, Sanket Partani, Christian Vielhaus, Martin Kasparick, Daniel F. Külzer, Friedrich Burmeister, Frank H. P. Fitzek, Hans D. Schotten, Gerhard Fettweis, Sławomir Stańczak

Abstract: The evolution of wireless communications into 6G and beyond is expected to rely on new machine learning (ML)-based capabilities. These can enable proactive decisions and actions from wireless-network components to sustain quality-of-service (QoS) and user experience. Moreover, new use cases in the area of vehicular and industrial communications will emerge. Specifically in the area of vehicle comm… ▽ More The evolution of wireless communications into 6G and beyond is expected to rely on new machine learning (ML)-based capabilities. These can enable proactive decisions and actions from wireless-network components to sustain quality-of-service (QoS) and user experience. Moreover, new use cases in the area of vehicular and industrial communications will emerge. Specifically in the area of vehicle communication, vehicle-to-everything (V2X) schemes will benefit strongly from such advances. With this in mind, we have conducted a detailed measurement campaign that paves the way to a plethora of diverse ML-based studies. The resulting datasets offer GPS-located wireless measurements across diverse urban environments for both cellular (with two different operators) and sidelink radio access technologies, thus enabling a variety of different studies towards V2X. The datasets are labeled and sampled with a high time resolution. Furthermore, we make the data publicly available with all the necessary information to support the onboarding of new researchers. We provide an initial analysis of the data showing some of the challenges that ML needs to overcome and the features that ML can leverage, as well as some hints at potential research studies. △ Less

Submitted 14 April, 2023; v1 submitted 20 December, 2022; originally announced December 2022.

Comments: 5 pages, 6 figures. Accepted for presentation at IEEE conference VTC2023-Spring. Available dataset at https://ieee-dataport.org/open-access/berlin-v2x

TSN-FlexTest: Flexible TSN Measurement Testbed (Extended Version)

Authors: Marian Ulbricht, Stefan Senk, Hosein K. Nazari, How-Hang Liu, Martin Reisslein, Giang T. Nguyen, Frank H. P. Fitzek

Abstract: Robust, reliable, and deterministic networks are essential for a variety of applications. In order to provide guaranteed communication network services, Time-Sensitive Networking (TSN) unites a set of standards for time-synchronization, flow control, enhanced reliability, and management. We design the TSN-FlexTest testbed with generic commodity hardware and open-source software components to enabl… ▽ More Robust, reliable, and deterministic networks are essential for a variety of applications. In order to provide guaranteed communication network services, Time-Sensitive Networking (TSN) unites a set of standards for time-synchronization, flow control, enhanced reliability, and management. We design the TSN-FlexTest testbed with generic commodity hardware and open-source software components to enable flexible TSN measurements. We have conducted extensive measurements to validate the TSN-FlexTest testbed and to examine TSN characteristics. The measurements provide insights into the effects of TSN configurations, such as increasing the number of synchronization messages for the Precision Time Protocol, indicating that a measurement accuracy of 15 ns can be achieved. The TSN measurements included extensive evaluations of the Time-aware Shaper (TAS) for sets of Tactile Internet (TI) packet traffic streams. The measurements elucidate the effects of different scheduling and shaping approaches, while revealing the need for pervasive network control that synchronizes the sending nodes with the network switches. We present the first measurements of distributed TAS with synchronized senders on a commodity hardware testbed, demonstrating the same Quality-of-Service as with dedicated wires for high-priority TI streams despite a 200% over-saturation cross traffic load. The testbed is provided as an open-source project to facilitate future TSN research. △ Less

Submitted 27 November, 2023; v1 submitted 18 November, 2022; originally announced November 2022.

Comments: 30 pages, 18 figures, 6 tables, IEEE TNSM, in print, 2024. Shorter version in print in IEEE Trans. on Network and Service Management (see related DOI below)

Functional Split of In-Network Deep Learning for 6G: A Feasibility Study

Authors: Jia He, Huanzhuo Wu, Xun Xiao, Riccardo Bassoli, Frank H. P. Fitzek

Abstract: In existing mobile network systems, the data plane (DP) is mainly considered a pipeline consisting of network elements end-to-end forwarding user data traffics. With the rapid maturity of programmable network devices, however, mobile network infrastructure mutates towards a programmable computing platform. Therefore, such a programmable DP can provide in-network computing capability for many appli… ▽ More In existing mobile network systems, the data plane (DP) is mainly considered a pipeline consisting of network elements end-to-end forwarding user data traffics. With the rapid maturity of programmable network devices, however, mobile network infrastructure mutates towards a programmable computing platform. Therefore, such a programmable DP can provide in-network computing capability for many application services. In this paper, we target to enhance the data plane with in-network deep learning (DL) capability. However, in-network intelligence can be a significant load for network devices. Then, the paradigm of the functional split is applied so that the deep neural network (DNN) is decomposed into sub-elements of the data plane for making machine learning inference jobs more efficient. As a proof-of-concept, we take a Blind Source Separation (BSS) problem as an example to exhibit the benefits of such an approach. We implement the proposed enhancement in a full-stack emulator and we provide a quantitative evaluation with professional datasets. As an initial trial, our study provides insightful guidelines for the design of the future mobile network system, employing in-network intelligence (e.g., 6G). △ Less

Submitted 14 November, 2022; originally announced November 2022.

A New Agent-Based Intelligent Network Architecture

Authors: Sisay Tadesse Arzo, Domenico Scotece, Riccardo Bassoli, Fabrizio Granelli, Luca Foschini, Frank H. P. Fitzek

Abstract: The advent of 5G and the design of its architecture has become possible because of the previous individual scientific works and standardization efforts on cloud computing and network softwarization. Software-defined Networking and Network Function Virtualization started separately to find their convolution into 5G network architecture. Then, the ongoing design of the future beyond 5G (B5G) and 6G… ▽ More The advent of 5G and the design of its architecture has become possible because of the previous individual scientific works and standardization efforts on cloud computing and network softwarization. Software-defined Networking and Network Function Virtualization started separately to find their convolution into 5G network architecture. Then, the ongoing design of the future beyond 5G (B5G) and 6G network architecture cannot overlook the pivotal inputs of different independent standardization efforts about autonomic networking, service-based communication systems, and multi-access edge computing. This article provides the design and the characteristics of an agent-based, softwarized, and intelligent architecture, which coherently condenses and merges the independent proposed architectural works by different standardization working groups and bodies. This novel work is a helpful means for the design and standardization process of the futureB5G and 6G network architecture. △ Less

Submitted 3 November, 2022; originally announced November 2022.

Comments: 7 pages, 6 figures

Neuromorphic Twins for Networked Control and Decision-Making

Authors: Holger Boche, Yannik N. Böck, Christian Deppe, Frank H. P. Fitzek

Abstract: We consider the problem of remotely tracking the state of and unstable linear time-invariant plant by means of data transmitted through a noisy communication channel from an algorithmic point of view. Assuming the dynamics of the plant are known, does there exist an algorithm that accepts a description of the channel's characteristics as input, and returns 'Yes' if the transmission capabilities pe… ▽ More We consider the problem of remotely tracking the state of and unstable linear time-invariant plant by means of data transmitted through a noisy communication channel from an algorithmic point of view. Assuming the dynamics of the plant are known, does there exist an algorithm that accepts a description of the channel's characteristics as input, and returns 'Yes' if the transmission capabilities permit the remote tracking of the plant's state, 'No' otherwise? Does there exist an algorithm that, in case of a positive answer, computes a suitable encoder/decoder-pair for the channel? Questions of this kind are becoming increasingly important with regards to future communication technologies that aim to solve control engineering tasks in a distributed manner. In particular, they play an essential role in digital twinning, an emerging information processing approach originally considered in the context of Industry 4.0. Yet, the abovementioned questions have been answered in the negative with respect to algorithms that can be implemented on idealized digital hardware, i.e., Turing machines. In this article, we investigate the remote state estimation problem in view of the Blum-Shub-Smale computability framework. In the broadest sense, the latter can be interpreted as a model for idealized analog computation. Especially in the context of neuromorphic computing, analog hardware has experienced a revival in the past view years. Hence, the contribution of this work may serve as a motivation for a theory of neuromorphic twins as a counterpart to digital twins for analog hardware. △ Less

Submitted 1 November, 2022; originally announced November 2022.

On the Need of Neuromorphic Twins to Detect Denial-of-Service Attacks on Communication Networks

Authors: Holger Boche, Rafael F. Schaefer, H. Vincent Poor, Frank H. P. Fitzek

Abstract: As we are more and more dependent on the communication technologies, resilience against any attacks on communication networks is important to guarantee the digital sovereignty of our society. New developments of communication networks tackle the problem of resilience by in-network computing approaches for higher protocol layers, while the physical layer remains an open problem. This is particularl… ▽ More As we are more and more dependent on the communication technologies, resilience against any attacks on communication networks is important to guarantee the digital sovereignty of our society. New developments of communication networks tackle the problem of resilience by in-network computing approaches for higher protocol layers, while the physical layer remains an open problem. This is particularly true for wireless communication systems which are inherently vulnerable to adversarial attacks due to the open nature of the wireless medium. In denial-of-service (DoS) attacks, an active adversary is able to completely disrupt the communication and it has been shown that Turing machines are incapable of detecting such attacks. As Turing machines provide the fundamental limits of digital information processing and therewith of digital twins, this implies that even the most powerful digital twins that preserve all information of the physical network error-free are not capable of detecting such attacks. This stimulates the question of how powerful the information processing hardware must be to enable the detection of DoS attacks. Therefore, in the paper the need of neuromorphic twins is advocated and by the use of Blum-Shub-Smale machines a first implementation that enables the detection of DoS attacks is shown. This result holds for both cases of with and without constraints on the input and jamming sequences of the adversary. △ Less

Submitted 29 October, 2022; originally announced October 2022.

Comments: submitted for publication

Network Functional Compression for Control Applications

Authors: Sifat Rezwan, Juan A. Cabrera, Frank H. P. Fitzek

Abstract: The trend of future communication systems is to aim for the steering and control of cyber physical systems. These systems can quickly become congested in environments like those presented in Industry 4.0. In these scenarios, a plethora of sensor data is transmitted wirelessly to multiple in network controllers that compute the control functions of the cyber physical systems. In this paper, we show… ▽ More The trend of future communication systems is to aim for the steering and control of cyber physical systems. These systems can quickly become congested in environments like those presented in Industry 4.0. In these scenarios, a plethora of sensor data is transmitted wirelessly to multiple in network controllers that compute the control functions of the cyber physical systems. In this paper, we show an implementation of network Functional Compression (FC) as a proof of concept to drastically reduce the data traffic in these scenarios. FC is a form of goal-oriented communication scheme in which the objective of the sender receiver pair is to transmit the minimum amount of information to compute a function at the receiver end. In our scenario, the senders transmit an encoded and compressed version of the sensor data to a destination, an in-network controller interested in computing as its target function, a PID controller. We show that it is possible to achieve compression rates of over 50% in some cases by employing FC. We also show that using FC in a distributed cascade fashion can achieve more significant compression rates while reducing computational costs. △ Less

Submitted 26 October, 2022; originally announced October 2022.

On the Need of Analog Signals and Systems for Digital-Twin Representations

Authors: Holger Boche, Ullrich J. Mönich, Yannik N. Böck, Frank H. P. Fitzek

Abstract: We consider the task of converting different digital descriptions of analog bandlimited signals and systems into each other, with a rigorous application of mathematical computability theory. Albeit very fundamental, the problem appears in the scope of digital twinning, an emerging concept in the field of digital processing of analog information that is regularly mentioned as one of the key enabler… ▽ More We consider the task of converting different digital descriptions of analog bandlimited signals and systems into each other, with a rigorous application of mathematical computability theory. Albeit very fundamental, the problem appears in the scope of digital twinning, an emerging concept in the field of digital processing of analog information that is regularly mentioned as one of the key enablers for next-generation cyber-physical systems and their areas of application. In this context, we prove that essential quantities such as the peak-to-average power ratio and the bounded-input/bounded-output norm, which determine the behavior of the real-world analog system, cannot generally be determined from the system's digital twin, depending on which of the above-mentioned descriptions is chosen. As a main result, we characterize the algorithmic strength of Shannon's sampling type representation as digital twin implementation and also introduce a new digital twin implementation of analog signals and systems. We show there exist two digital descriptions, both of which uniquely characterize a certain analog system, such that one description can be algorithmically converted into the other, but not vice versa. △ Less

Submitted 9 October, 2022; originally announced October 2022.

An Analytical Study on Functional Split in Martian 3D Networks

Authors: Stefano Bonafini, Claudio Sacchi, Riccardo Bassoli, Fabrizio Granelli, Koteswararao Kondepu, Frank H. P. Fitzek

Abstract: As space agencies are planning manned missions to reach Mars, researchers need to pave the way for supporting astronauts during their sojourn. This will also be achieved by providing broadband and low-latency connectivity through wireless network infrastructures. In such a framework, we propose a Martian deployment of a 3-Dimensional (3D) network acting as Cloud Radio Access Network (C-RAN). The s… ▽ More As space agencies are planning manned missions to reach Mars, researchers need to pave the way for supporting astronauts during their sojourn. This will also be achieved by providing broadband and low-latency connectivity through wireless network infrastructures. In such a framework, we propose a Martian deployment of a 3-Dimensional (3D) network acting as Cloud Radio Access Network (C-RAN). The scenario consists, mostly, of unmanned aerial vehicles (UAVs) and nanosatellites. Thanks to the thin Martian atmosphere, CubeSats can stably orbit at very-low-altitude. This allows to meet strict delay requirements to split functions of the baseband processing between drones and CubeSats. The detailed analytical study, presented in this paper, confirmed the viability of the proposed 3D architecture, under some constraints and trade-off concerning the involved Space communication infrastructures, that are discussed in detail. △ Less

Submitted 6 June, 2022; originally announced July 2022.

Comments: Initial version submitted to IEEE Transactions on Aerospace and Electronic Systems

Reference Network and Localization Architecture for Smart Manufacturing based on 5G

Authors: Stephan Ludwig, Doris Aschenbrenner, Marvin Scharle, Henrik Klessig, Michael Karrenbauer, Huanzhuo Wu, Maroua Taghouti, Pedro Lozano, Hans D. Schotten, Frank H. P. Fitzek

Abstract: 5G promises to shift Industry 4.0 to the next level by allowing flexible production. However, many communication standards are used throughout a production site, which will stay so in the foreseeable future. Furthermore, localization of assets will be equally valuable in order to get to a higher level of automation. This paper proposes a reference architecture for a convergent localization and com… ▽ More 5G promises to shift Industry 4.0 to the next level by allowing flexible production. However, many communication standards are used throughout a production site, which will stay so in the foreseeable future. Furthermore, localization of assets will be equally valuable in order to get to a higher level of automation. This paper proposes a reference architecture for a convergent localization and communication network for smart manufacturing that combines 5G with other existing technologies and focuses on high-mix low-volume application, in particular at small and medium-sized enterprises. The architecture is derived from a set of functional requirements, and we describe different views on this architecture to show how the requirements can be fulfilled. It connects private and public mobile networks with local networking technologies to achieve a flexible setup addressing many industrial use cases. △ Less

Submitted 4 April, 2022; v1 submitted 1 April, 2022; originally announced April 2022.

Comments: 10 pages; submitted to 6th International Conference on System-Integrated Intelligence. Intelligent, flexible and connected systems in products and production, 7-9 September Genova, Italy

In-Network Processing for Low-Latency Industrial Anomaly Detection in Softwarized Networks

Authors: Huanzhuo Wu, Jia He, Máté Tömösközi, Zuo Xiang, Frank H. P. Fitzek

Abstract: Modern manufacturers are currently undertaking the integration of novel digital technologies - such as 5G-based wireless networks, the Internet of Things (IoT), and cloud computing - to elevate their production process to a brand new level, the level of smart factories. In the setting of a modern smart factory, time-critical applications are increasingly important to facilitate efficient and safe… ▽ More Modern manufacturers are currently undertaking the integration of novel digital technologies - such as 5G-based wireless networks, the Internet of Things (IoT), and cloud computing - to elevate their production process to a brand new level, the level of smart factories. In the setting of a modern smart factory, time-critical applications are increasingly important to facilitate efficient and safe production. However, these applications suffer from delays in data transmission and processing due to the high density of wireless sensors and the large volumes of data that they generate. As the advent of next-generation networks has made network nodes intelligent and capable of handling multiple network functions, the increased computational power of the nodes makes it possible to offload some of the computational overhead. In this paper, we show for the first time our IA-Net-Lite industrial anomaly detection system with the novel capability of in-network data processing. IA-Net-Lite utilizes intelligent network devices to combine data transmission and processing, as well as to progressively filter redundant data in order to optimize service latency. By testing in a practical network emulator, we showed that the proposed approach can reduce the service latency by up to 40%. Moreover, the benefits of our approach could potentially be exploited in other large-volume and artificial intelligence applications. △ Less

Submitted 7 December, 2021; originally announced December 2021.

In-Network Processing Acoustic Data for Anomaly Detection in Smart Factory

Authors: Huanzhuo Wu, Yunbin Shen, Xun Xiao, Artur Hecker, Frank H. P. Fitzek

Abstract: Modern manufacturing is now deeply integrating new technologies such as 5G, Internet-of-things (IoT), and cloud/edge computing to shape manufacturing to a new level -- Smart Factory. Autonomic anomaly detection (e.g., malfunctioning machines and hazard situations) in a factory hall is on the list and expects to be realized with massive IoT sensor deployments. In this paper, we consider acoustic da… ▽ More Modern manufacturing is now deeply integrating new technologies such as 5G, Internet-of-things (IoT), and cloud/edge computing to shape manufacturing to a new level -- Smart Factory. Autonomic anomaly detection (e.g., malfunctioning machines and hazard situations) in a factory hall is on the list and expects to be realized with massive IoT sensor deployments. In this paper, we consider acoustic data-based anomaly detection, which is widely used in factories because sound information reflects richer internal states while videos cannot; besides, the capital investment of an audio system is more economically friendly. However, a unique challenge of using audio data is that sounds are mixed when collecting thus source data separation is inevitable. A traditional way transfers audio data all to a centralized point for separation. Nevertheless, such a centralized manner (i.e., data transferring and then analyzing) may delay prompt reactions to critical anomalies. We demonstrate that this job can be transformed into an in-network processing scheme and thus further accelerated. Specifically, we propose a progressive processing scheme where data separation jobs are distributed as microservices on intermediate nodes in parallel with data forwarding. Therefore, collected audio data can be separated 43.75% faster with even less total computing resources. This solution is comprehensively evaluated with numerical simulations, compared with benchmark solutions, and results justify its advantages. △ Less

Submitted 4 October, 2021; originally announced October 2021.