Institution profile

Technische Universität Braunschweig

Academic institutioneurope · de
Official website
Research library156linked papers
Opportunities0open roles
Selected work

Representative Papers

A Case Study on Evaluating Encodings Between Process Calculi

Feb 12, 2025

This paper systematically evaluates the quality of encodings between process calculi, specifically addressing the fidelity of two classical translations—from synchronous to asynchronous π-calculus—namely the Honda–Tokoro and Boudol encodings—under various behavioral equivalences. Method: We conduct a dual-dimensional verification within a unified formal framework, integrating Gorla’s five criteria for valid encodings with a hierarchy of semantic equivalences: trace equivalence, failure simulation, observational equivalence, and strong/weak bisimulation. Contribution/Results: Our analysis reveals that the Honda–Tokoro encoding satisfies only the weakest criterion—trace equivalence—whereas the Boudol encoding preserves the strictly stronger failure simulation equivalence, demonstrating significantly higher behavioral fidelity. This work establishes the first empirical benchmark for assessing encoding quality in process calculi and provides a reusable, principled methodology grounded in both syntactic validity criteria and semantic strength.

2 citationsRead paper

Optimum Network Slicing for Ultra-reliable Low Latency Communication (URLLC) Services in Campus Networks

Apr 17, 2023International Workshop on the Design of Reliable Communication Networks

To address the stringent ultra-low latency (<10 ms) and ultra-high reliability (≥99.999%) requirements of URLLC traffic in industrial campus networks, this paper proposes a vertical RAN slicing framework with strict resource isolation. Methodologically, it innovatively integrates dynamic UPF deployment into RAN slicing modeling—enabling flexible scheduling of URLLC flows where source nodes are known but destination nodes are unknown—and formulates a mixed-integer linear programming (MILP) model incorporating hard URLLC constraints to jointly optimize RAN functional split, deployment locations, and dynamic UPF orchestration. Experimental validation on a real-world campus network demonstrates that the proposed approach reduces end-to-end latency by 32% compared to baseline methods, achieves the target reliability of 99.999%, and supports coexistence of multiple slices with strict physical resource isolation.

2 citationsRead paper

Lessons Learned from the URGENT 2024 Speech Enhancement Challenge

Jun 02, 2025

This paper addresses long-overlooked bottlenecks in speech enhancement (SE): (1) bandwidth mismatch and implicit label noise in training corpora; (2) insufficient robustness under extreme conditions (e.g., speaker overlap, high noise/reverberation) and lack of quantifiable metrics for hard samples; and (3) poor correlation between single objective metrics and subjective perceptual quality. We propose a data quality diagnostic framework with bandwidth consistency verification, revealing—for the first time—systematic effective bandwidth deviations and >15% label noise across mainstream SE corpora. Furthermore, we introduce a difficulty-aware, multi-metric fusion evaluation framework that integrates objective measures with MOS-mapped weighted aggregation. Experiments demonstrate a 32% improvement in Pearson correlation (r) between automatic assessment and human judgments, significantly enhancing the reliability and interpretability of SE system development.

1 citations1 influentialRead paper

Rate-Reliability Tradeoff for Deterministic Identification over Gaussian Channels

Feb 12, 2026

This study addresses the trade-off between rate and reliability in deterministic identification (DI) over continuous-output Gaussian channels. Extending beyond prior work confined to discrete-output settings, this paper establishes the first theoretical framework for DI in general linear Gaussian channels, characterizing the fundamental rate-reliability performance limits. By integrating information-theoretic analysis with the Gaussian channel model within the DI paradigm, the work reveals a profound structural similarity between continuous and discrete cases. These results lay a rigorous foundation for evaluating and deploying DI mechanisms in future ultra-reliable low-latency communication systems, demonstrating their potential to enhance communication efficiency.

1 citationsRead paper

ICASSP 2026 URGENT Speech Enhancement Challenge

Jan 20, 2026

This work proposes the first unified challenge framework that integrates general-purpose speech enhancement with speech quality assessment, aiming to address the robustness and generalization of systems under unknown distortion types, domains, and input conditions. By leveraging multi-source, multi-scenario training data, a standardized evaluation protocol, and baseline models, the framework enables fair comparisons between end-to-end deep learning approaches and traditional signal processing methods. The challenge features two complementary tracks: Track 1 focuses on general enhancement performance, while Track 2 incorporates objective quality assessment. The initiative attracted over 80 registered teams, with 29 submitting valid solutions, significantly advancing community-wide research and progress in general-purpose speech enhancement.

1 citationsRead paper
Recent publications

Latest Papers