TU Berlin

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Research Vision

Research Objectives

Our research objectives include adaptive wireless networking (sub-6GHz, mmWave, visible light, molecular communication) and wireless-based sensing with applications in ad hoc and sensor networks, the Internet of Things, and Cyber-Physical Systems. Our current projects focus on novel and innovative concepts for 5G/6G communication systems, digital smart cities of tomorrow, and vehicular applications, emphasizing on communication technologies and cooperative assistance systems.

Research Focus

Heterogeneous Wireless and Mobile Systems
We are working on methods ranging from coexistence to collaboration in unlicensed spectrum bands. Here, we are particularly interested in new radio resource and interference management approaches as well as techniques for self-organization and self-adaptation.
Cross-technology communication (CTC) is a means to bridge the gap between devices and standards. This is becoming particularly relevant for enabling control channels using between heterogeneous networks and to support IoT devices using narrow-band communication from wide-band OFDMA-based systems.
We also make use of RF-signals for indoor and outdoor localization. The challenge is the fusion of localization information from diverse sources such as inertial measurement units (IMU). In this line of research, we are also interested in joint communication and sensing.

Beyond RF / Unconventional Communication
Going beyond standard sub-6GHz channels, we are working on line of sight communication technologies such as millimeter wave (mmWave) and visible light communication (VLC). Research challenges include the characterization of channels based on empirical measurements to develop realistic simulation models, as well as the design of heterogeneous communication protocols using VLC and/or mmWave in combination with sub-6GHz. We are also investigating joint communication and sensing using both mmWave and VLC.
Going well beyond conventional communication, we explore nano communication and molecular communication channels. This includes the integration of in-body nano communication and body area networks for healthcare applications. Here, ultrasound and particle dispersion are good alternatives to electromagnetic communication. Macroscopic molecular communication, in contrast, helps establishing communication in industrial environments such as water tanks, and even allows studying the duality of air-based molecular communication and pathogen distribution through aerosols.

Intelligent Transportation Systems (ITS)
The field of vehicular networking (V2X) and intelligent transportation systems has been on our research agenda since a long time. More recently, we are interested in safety systems for vulnerable road users. Here, human-in-the-loop testing in our virtual cycling environment can be the key for next generation safety solution.
Platooning, i.e., cooperative automated driving of vehicle convoys, needs to be supported by adaptive heterogeneous communications and optimal platoon formation algorithms.
Vehicular micro clouds help to support MEC in 5G networks and beyond. These micro clouds are made of cars dynamically joining and leaving the cluster. Offloading can now be performed in a fully distributed way, still supported by the cloud and data centers.
Our research strongly requires holistic V2X Simulation. We are investigating real-time V2X simulation as well as the integration of connected electric mobility.

Machine Learning and Networking
Wireless communication networks have evolved into complex and dynamic systems. The numbers of knobs to be optimized are huge, e.g., in WiFi and LTE standards. Thus, unconventional approaches needed to master the complexity of control and management. We explore machine Learning algorithms like reinforcement learning (RL), which are very well suited for such applications. RL is particularly promising for hard problems like co-existence of heterogeneous technologies. Still, challenges like long learning time need to be solved. In a further step, we study transfer learning for training in simulation and use of the trained models in real world. We developed multiple Open AI Gym-based toolkits, e.g., ns3gym (network simulation), grGym (software defined radio), and VeinsGym (intelligent transportation systems).

Research Methodology

Modeling, simulation, and experimentation
Our research methodology is covering the full range from modeling to simulation to real-world experimentation. To support the research community, we make almost all developed software and measurement data available as Open Source and Open Data, respectively.
In the domain of simulation-based performance evaluation, we are particularly proud of our widely used frameworks. This includes Veins, Plexe, and VeinsGym for vehicular networking, EVI for Real-time coupling with ego cars, VCE for integrating vulnerable road users, and Pogona for simulating molecular communication.
As a systems-focused research group, we build systems - at least prototypes - for real-world experiments and field tests. We make use of COTS platform-based systems using standard chipsets for WiFi5 and WiFi6 experiments; we developed OpenC2X, an embedded Linux based platform for standard-conform field tests; and we provide libraries for GNU Radio-based software defined radio such as gr-ieee802-11 and gr-ieee802-15-4.

Further Information

Current Research Partners and Funding Organizations

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