News and Announcements

  • New Elsevier Computer Communications article

    October 16, 2025

    Operator Coexistence in IRS-Assisted mmWave Networks: A Wideband Approach Our article has been accepted for publication in Elsevier Computer Communications. Intelligent reconfigurable surfaces (IRSs) present a promising solution to these challenges by enhancing signal coverage and directing reflections, which also contribute to minimize loss. However, there are multiple challenges associated with IRS, which have to be addressed before full incorporation of this technology into existing networks. A key issue arises from the inability of IRS to filter out non-target signals from other frequency bands due to lack of bandpass filtering. In areas where multiple wireless operators are spatially nearby, even if they use different frequency bands, this may cause unwanted reflections that may degrade their communication performances. To address this challenge, we previously proposed a solution, which relied on partitioning an IRS into sub-surfaces (sub_IRS) and dynamically assigning operators to these sub_IRS. Results have shown that a proper assignment of wireless operators to sub_IRS can improve the overall performance compared to a random assignment. In this paper, we introduce a wideband approach, demonstrating that the impact from unwanted reflections can be mitigated by using wideband channels, as the average signal to noise ratio (SNR) across subcarriers is less adversely affected. This approach leverages frequency diversity to reduce SNR variance, as some of the subcarriers may be negatively affected while others benefit, resulting in maintaining a more consistent and robust system performance in the presence of IRS-induced unwanted reflections.
    (link to more information)

  • Paper and Poster Presentation at IEEE LCN 2025

    October 15, 2025

    Simon Schmitz-Heinen and Sascha Rösler presented our paper Ce-Fi: Centralized Wi-Fi over Packet-Fronthaul and our poster Improving WiFi Ranging Through Frequency Diversity and Mobility at the Conference on Local Computer Networks (LCN), Sydney, Australia. The first work investigates Ce-Fi, a centralized Wi-Fi architecture operating over a packet-based fronthaul (FH) connecting the central unit with the remote radio heads. Ce-Fi employs a two-level design with two bands: the network discovery and user association is handled standard compliantly on one band while another band is used for the actual data transmission with the centralized Wi-Fi. To tolerate the FH-induced delay, we propose minor changes to the 802.11 medium access control protocol like NAV extension and the usage of a piggybacking mechanism enabling the C-RAN-AP to transmit without prior channel contention. The poster presents HopFTM to enhance FTM ranging accuracy by leveraging frequency diversity and space diversity through mobility. Specifically, HopFTM performs ranging on multiple radio channels. Additionally, in a mobile scenario, ranging is performed at multiple locations. Our experimental results using low-cost ESP32-S3 hardware reveal that selecting the smallest RTT value from all measured channels significantly improves accuracy, especially in environments with strong multi-path effects or non-line-of-sight conditions. In a static scenario by using the smallest RTT from four channels, we were able to reduce the median ranging error by 4× from 120 cm to 30 cm while the worst-case error was decreased from 15 m to 10 m, compared to traditional single-channel approach. In a mobile scenario, ranging measurements taken at different locations outside the decorrelation distance can also be fused. Our simulation shows that taking the smallest RTT value over multiple positions can improve FTM ranging error from 1.8 m to 0.76 m.

  • Youming Tao just defended his PhD - congratulations!

    October 13, 2025

    Youming Tao successfully defended his PhD on October 13, 2025. His dissertation is titled "Trustworthy Collaborative Machine Learning for Edge AI: Privacy, Unlearning, and Robustness". He was awarded a Dr.-Ing. degree (with distinction) from TU Berlin.
    (link to more information)

  • TKN/CCS at NetSys 2025

    September 04, 2025

    The TKN team together with CCS alumni met at NetSys 2025. We had a very successful conference, presenting recent reseaerch results, receiving as many as four awards, and meeting lots of friends and collaborators.

  • Awards and Presentations at NetSys 2025

    September 03, 2025

    The TKN team received multiple awards for best bachelor and master theses from the German GI/ITG SIG on Communication and Distributed Systems. In addition, team members gave highlight talks on hot topics in networking and communications at NetSys 2025. Rebecca C. Pampu received a best thesis award for her Bachelor thesis Identification of the Signal Source among Multiple Simultaneous Senders in an Air-based Molecular Communication Channel. Isabel von Stebut received a best thesis award for her Bachelor thesis Resilience through Cross-Technology-Communication. Lisa Y. Debus received a best thesis award for her Master thesis Decoding Media Modulation Sharply: A Reinforcement Learning-based Receiver. Youming Tao presented a highlights talk of our recent paper Communication Efficient and Provable Federated Unlearning. Anatolij Zubow presented a highlights talk of our recent paper Hybrid-Fidelity: Utilizing IEEE 802.11 MIMO for Practical Aggregation of LiFi and WiFi.

  • Best Paper Award at ReNeSys 2025

    September 01, 2025

    Our team member Sascha Rösler received a Best Paper Award for our paper Robust LoRa via Repetition in Frequency through Signal Emulation using WiFi at teh 1st Workshop on Resilient Networks and Systems (ReNeSys 2025).

  • ReNeSys 2025 at NetSys

    September 01, 2025

    Dr. Doganalp Ergenc organized the 1st Workshop on Resilient Networks and Systems (ReNeSys), held in conjunction with NetSys 2025 in Ilmenau. The workshop featured several engaging presentations from the authors of accepted papers, complemented by two keynote talks that offered inspiring insights into the security and resilience of next-generation networks. You can visit the workshop website for more details!

  • Tutorial Lecture at NetSys 2025

    September 01, 2025

    Our group member Jorge Torres Gomez and Pit Hofman from TU Dresden, gave a tutorial lecture on neural networks (NN) and the Internet of Bio-Nano-Things (IoBNT). The tutorial took place at the International Conference on Networked Systems (NetSys) in TU Ilmenau, Sept. 1-4, Germany. The tutorial highlighted the essentials of NN-driven communication and computing approaches, with a primary focus on the bio-inspired MC paradigm. We dedicated sessions to integrating NN into practical testbeds and generating real-world datasets.

  • New IEEE Communications Surveys & Tutorials article

    August 30, 2025

    Our article Exhaled Breath Analysis Through the Lens of Molecular Communication: A Survey" has been accepted for publication in IEEE Communications Surveys & Tutorials. 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 humans 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.
    (link to more information)

  • New IEEE Transactions on Molecular, Biological and Multi-Scale Communications article

    August 23, 2025

    Our article Machine Learning-Driven Localization of Infection Sources in the Human Cardiovascular System has been accepted for publication in IEEE Transactions on Molecular, Biological and Multi-Scale Communications. In vivo localization of infection sources is essential for effective diagnosis and targeted disease treatment. In this work, we leverage machine learning models to associate the temporal dynamics of biomarkers detected at static gateway positions with different infection source locations. In particular, we introduce a simulation that models infection sources, the release of biomarkers, and their decay as they flow through the bloodstream. From this, we extract time-series biomarker data with varying decay rates to capture temporal patterns from different infection sources at specific gateway positions. We then train a stacked ensemble model using LightGBM and BernoulliNB to analyze biomarker time-series data for classification. Our results reveal that higher biomarker degradation rates significantly reduce the localization accuracy by limiting the biomarker signal detected at the gateways. A fivefold increase in decay rate lowers the mean cross-validation accuracy from ∼92% to ∼66%.
    (link to more information)

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Last modified: 2024-04-28