2025 Swedish Communication Technologies Workshop (Swe-CTW 2025)
Swe-CTW 2025 will bring together researchers and research students in the general area of communication technologies and related areas. The two-day workshop provides an opportunity for researchers and research students to gather in a largely informal setting to share ideas, make contacts, and foster new collaborative links for the future. This year’s workshop is based on the previous Swe-CTW held in Stockholm, Lund, Göteborg, Västerås, Karlstad and Sundsvall and modeled on similar successful events in Denmark and Australia, emphasizing the active participation of young researchers and research students. In addition to the workshop, the aim is to have two tutorials.
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- Linköping University
- Campus Valla
- Linköping, Ostergotlands lan
- Sweden 581 83
- Building: B-building
- Room Number: Ada Lovlace
- Click here for Map
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- Co-sponsored by Linköping University
- Starts 31 July 2025 10:00 PM UTC
- Ends 22 October 2025 07:00 PM UTC
- No Admission Charge
Speakers
Nikolaos Pappas
From Information Freshness to Semantics of Information and Goal-oriented Communications
In this talk will identify and discuss technical challenges and recent results related to task-oriented and semantics-aware communications for future wireless networks. The talk is mainly divided into two parts. In the first part, we will provide the motivation and discuss the current approaches towards semantics-aware goal-oriented communications, such as earlier studies that consider the age and value of information. Then, we will consider the topic beyond the age of information. We will present results in real-time remote tracking and actuation, industrial IoT, and autonomous systems. We will conclude the talk by providing a future outlook of task-oriented and semantics-aware communication and networks.
Biography:
Nikolaos Pappas (Senior Member, IEEE) received the first B.Sc. degree in computer science, the second B.Sc. degree in mathematics, the M.Sc. degree in computer science, and the Ph.D. degree in computer science from the University of Crete, Greece, in 2005, 2012, 2007, and 2012, respectively. From 2005 to 2012, he was a Graduate Research Assistant with the Telecommunications and Networks Laboratory, Institute of Computer Science, Foundation for Research and Technology–Hellas, Heraklion, Greece; and a Visiting Scholar with the Institute of Systems Research, University of Maryland at College Park, College Park, MD, USA. From 2012 to 2014, he was a Post-Doctoral Researcher with the Department of Telecommunications, CentraleSupec, France. He is currently an Associate Professor with the Department of Computer and Information Science, Linköping University, Linköping, Sweden. His main research interests include the field of wireless communication networks, with an emphasis on semantics-aware communications, energy harvesting networks, network-level cooperation, age of information, and stochastic geometry. He has served as the Symposium Co-Chair for the IEEE International Conference on Communications in 2022. He was the general chair for the 23rd International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks (WiOpt 2025). He is an Area Editor of the IEEE Open Journal of the Communications Society and an Expert Editor of invited papers of the IEEE Communications Letters. He is Associate Editor for four IEEE Transactions journals.
Bile Peng
Problem-Specific Unsupervised Machine Learning for Communication System Optimization
As wireless communication systems become increasingly complex, optimizing their performance has become a significant challenge. In this context, unsupervised machine learning is gaining importance due to its ability to autonomously optimize system performance without requiring labeled data. This tutorial introduces a framework for using unsupervised learning in system optimization combined with our domain knowledge in wireless communication. In particular, we introduce the model-based learning with known system models. We focus on techniques to address nonconvex problems with multiple local optima, combinatorial problems with discrete optimization variables, specialized neural network architectures tailored to problem-specific properties, and strategies to combine analytical methods with machine learning. These approaches leverage analytical methods and machine learning, collectively offer powerful tools for managing the growing intricacies of wireless communication systems.
Biography:
Bile Peng (Senior Member, IEEE) received the Ph.D. degree with distinction from the Institute of Communications Technology, Technische Universität Braunschweig in 2018. He has been a Postdoctoral researcher in the Chalmers University of Technology, Sweden from 2018 to 2019, a development engineer at IAV GmbH, Germany from 2019 to 2020. Currently, he is a Postdoctoral researcher in Institute of Communications Technology, Technische Universität Braunschweig, Germany. His research interests include Bayesian inference and machine learning algorithms for signal processing and resource allocation of wireless communication systems. He received the IEEE vehicular technology society Neal Shepherd memorial best propagation paper award twice (2019 and 2022).
Khac-Hoang Ngo
Type-based Unsourced Multiple Access
We introduce type-based unsourced multiple access (TUMA), a framework in which multiple devices track the state of physical/digital processes, quantizes this state, and communicates it to a common receiver through a shared channel in an uncoordinated manner. The receiver aims to estimate the type of the states, i.e., the set of states and their multiplicity in the sequence of states reported by all devices. Such a scenario is relevant in several applications, including over-the-air digital federated learning and multi-target positioning. We present fundamental information-theoretic bounds to quantify the performance achievable over this channel, as well as practical algorithms to approach these bounds.
Biography:
Khac-Hoang Ngo received the B.Eng. degree (Hons.) in electronics and telecommunications from University of Engineering and Technology, Vietnam National University, Hanoi, Vietnam, in 2014; and the M.Sc. degree (Hons.) and Ph.D. degree in wireless communications from CentraleSupélec, Paris-Saclay University, France, in 2016 and 2020, respectively. His Ph.D. research was also conducted at the Mathematical and Algorithmic Sciences Laboratory, Paris Research Center, Huawei Technologies France. From September 2020 to August 2024, he was a postdoctoral researcher with Communication Systems Group at Chalmers University of Technology, Sweden. Since September 2024, he has been an Assistant Professor with the Division of Communication Systems at Linköping University, Sweden. His research interests include wireless communications, information theory, and machine learning, with an emphasis on massive random access, privacy of machine learning, information freshness, MIMO systems, and noncoherent communications.