News and Announcements

• Paper Presentation at IEEE ICNC 2025

  February 19, 2025
  
  Christos Laskos presented our paper, Wi-Fi Ranging under Interference at the IEEE International Conference on Computing, Networking and Communications (ICNC 2025) in Honolulu, HI. In this paper, we demonstrate that time of arrival (ToA)-based ranging, utilizing the MUSIC super-resolution algorithm, is severely impacted by cross-technology and co-channel interference. This is due to the fact that the channel state information (CSI) obtained in the presence of interference includes not only the characteristics of the channel but also the interference itself. This corrupted CSI leads to persistent ToA errors.
  (link to more information)

• New Elsevier High-Confidence Computing article

  February 19, 2025
  
  Our article Task Migration with Deadlines using Machine Learning-based Dwell Time Prediction in Vehicular Micro Clouds has been accepted for publication in Elsevier High-Confidence Computing. Edge computing is becoming ever more relevant to offload compute-heavy tasks in vehicular networks. In this context, the concept of vehicular micro clouds (VMCs) has been proposed to use compute and storage resources on nearby vehicles to complete computational tasks. As many tasks in this application domain are time critical, offloading to the cloud is prohibitive. Additionally, task deadlines have to be dealt with. This paper addresses two main challenges. First, we present a task migration algorithm supporting deadlines in vehicular edge computing. The algorithm is following the earliest deadline first model but in presence of dynamic processing resources, i.e., vehicles joining and leaving a VMC. This task offloading is very sensitive to the mobility of vehicles in a VMC, i.e., the so-called dwell time a vehicles spends in the VMC. Thus, secondly, we propose a machine learning-based solution for dwell time prediction. Our dwell time prediction model uses a random forest approach to estimate how long a vehicle will stay in a VMC. Our proposed approach is able to realize low-delay and low-failure task migration in dynamic vehicular conditions, advancing the state of the art in vehicular edge computing.
  (link to more information)

• New IEEE/ACM Transactions on Networking article

  February 18, 2025
  
  Our article Jamming-Resilient Physical-to-Virtual Communications in Digital Twin Edge Networks has been accepted for publication in IEEE/ACM Transactions on Networking. As an integration of digital twin and edge computing, the digital twin edge networks (DITENs) have been proposed in recent years to fill the gap between physical edge networks and digital systems. Meanwhile, the multi-access wireless environments in edge computing make it hard to provide ultra-reliable and low-latency communications for digital twin, especially when the jamming attacks can be launched by the adversaries. This paper studies the jamming-resilient physical-to-virtual communication (PTVC) problem in DITENs despite strong cooperative jamming. Note that the previous jamming models mainly focus on the jamming behaviors from an individual adversary and are restricted by the energy budget limitation and uniform jamming assumption. In this paper, we consider a more comprehensive jamming model, in which f adversaries can cooperatively launch their jamming attacks in totally kwireless channels with unlimited power budget and non-uniform jamming signals. Both of the theoretical results and empirical simulations are conducted to show the resilience of our algorithms despite such a strong cooperative jamming model.
  (link to more information)

• New Elsevier Computer Networks article

  February 16, 2025
  
  Our article XAInomaly: Explainable and Interpretable Deep Contractive Autoencoder for O-RAN has been accepted for publication in Elsevier Computer Networks. Generative Artificial Intelligence (AI) techniques have become integral part in advancing next generation wireless communication systems by enabling sophisticated data modeling and feature extraction for enhanced network performance. In the realm of open radio access networks (O-RAN), characterized by their disaggregated architecture and heterogeneous components from multiple vendors, the deployment of generative models offers significant advantages for network management such as traffic analysis, traffic forecasting and anomaly detection. In this study, we introduce the XAInomaly framework, an explainable and interpretable Semi-supervised (SS) Deep Contractive Autoencoder (DeepCAE) design for anomaly detection in O-RAN. Our approach leverages the generative modeling capabilities of our SS-DeepCAE model to learn compressed, robust representations of normal network behavior, which captures essential features, enabling the identification of deviations indicative of anomalies. To address the black-box nature of deep learning models, we propose reactive Explainable AI (XAI) technique called fastshap-C, which is providing transparency into the model's decision-making process and highlighting the features contributing to anomaly detection.
  (link to more information)

• New International Journal of Microwave and Wireless Technologies article

  February 10, 2025
  
  Our article Fast Identification and Clustering of Multi-Path Components for Multi-band Industrial Wireless Channels has been accepted for publication in International Journal of Microwave and Wireless Technologies. Multi-path components are both the challenge and the resources to exploit in high-frequency wireless communication, especially in environment with complex reflections. To this end, identifying and clustering multi-path components is the foundation in tackling the challenges and boosting the utilization with reliable and correct information. Past research focuses either on extracting the path information, or on clustering the extracted components. In this paper, we propose a complete work flow that performs identification as well as clustering of multi-path components. We extend our previous work in clustering algorithm to indoor propagation measurements of three different frequency bands, as well as multiple transmitter-receiver locations. The ease of application highlights the wide-applying potential of high-frequency communication.
  (link to more information)

• New staff member: Ahmed Hasan Ansari

  February 10, 2025
  
  We welcome Ahmed Hasan Ansari who joined our group in February 2025.
  

• Paper Presentation at IEEE WONS 2025

  January 29, 2025
  
  Dr. Doganalp Ergenc presented our paper, "An Open-Source Implementation of Wi-Fi 7 Multi-Link Operation in OMNeT++," at the 20th IEEE Wireless On-demand Network Systems and Services Conference (WONS 2025) in Hintertux, Austria. In this paper, we introduce an open-source implementation of Wi-Fi 7 Multi-Link Operation (MLO), a key feature of the latest Wi-Fi standard. Developed within the widely used network simulator OMNeT++, our implementation demonstrates the throughput and reliability benefits of MLO in a small-scale simulation setup. The source code is available in our GitHub repository.
  (link to more information)

• Falko Dressler elevated to ACM Fellow

  January 22, 2025
  
  We congratulate Falko Dressler for being elevated to ACM Fellow with the citation "For contributions to foundations of self-organization in wireless communication protocols in IoT and vehicular applications". New York, NY, January 22, 2025 – ACM, the Association for Computing Machinery, has named 55 Fellows for transformative contributions to computing science and technology. All the 2024 inductees are longstanding ACM Members whose accomplishments were selected by their peers for making possible the computing technologies we use every day.
  (link to more information)

• New IEEE Communications Standards Magazine article

  January 09, 2025
  
  Our article Empowering Smart Factories with O-RAN has been accepted for publication in IEEE Communications Standards Magazine. It is envisioned that 6G mobile networks will enhance and majorly empower the Industry 4.0 paradigm, evolving towards smart factories with optimized and customized services. Especially the smart factory scenario with high-capacity data communication, which requires the usage of new portions of the electromagnetic spectrum (mmWave/sub-THz), is presenting us with new challenges, both in communications and networking. This article discusses the new challenges arising from high-capacity data communications in smart factories. It proposes extensions to the current Open Radio Access Network (O-RAN) standards for 6G networks to enable further evolution of Industry 4.0 and beyond. We motivate the need for real-time functionalities in O-RAN and an extended interface to the user equipment (UE) to allow for its fine-grained control.
  

• New staff member: Simon Schmitz-Heinen

  January 06, 2025
  
  We welcome Simon Schmitz-Heinen who joined our group in January 2025.
  

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