6G Mobile Communications

Combating climate change is one of the central tasks for humanity in the 21st century. The Paris Agreement and the European Green Deal commit the economy and society to become CO₂-neutral by 2050 at the latest – an ambitious goal to which mobile communications must also contribute. Although wireless communication becomes more efficient with each generation, 6G risks – as is the case with 5G – losing these benefits as the demand for data and thus the need for electricity will grow rapidly in the 2030s. Consequently, accompanying measures must be developed that decouple data volume from energy consumption. The formula is: More performance, less power.

Decarbonizing mobile communications is one of our core concerns. We apply targeted methods where particularly significant effects are expected. Therefore, our research activities focus on base stations, which are responsible for over 70 percent of the energy consumption of networks. The key is network energy savings: Certain components of the base stations are intelligently put into different states of wakefulness and sleep, so that the energy consumption can be reduced at any time depending on the volume of data transmitted, without affecting the users. To identify, assess, and refine the most effective methods in this area, we are working on a 6G-capable simulator for network energy savings. 

With 6G, an always available system is emerging that ensures access to the edge and cloud in every environment and situation. This hyperconnectivity is hardly manageable with conventional methods – autonomous networks are required so that the massive volume of data can be coordinated in real time and without interference. The latest breakthroughs in Artificial Intelligence thus become the central driver of the sixth generation. An AI-capable mobile communications system undergoes self-organized and self-optimized learning processes that enable the network to make intelligent decisions and solve problems. However, a challenge lies in tailoring the AI methods to the specific conditions of the upcoming standard.

A key area is neuromorphic computing technologies such as spiking neural networks, which mimic the functioning of the human brain and transmit data in the form of pulses. We are exploring how these neural networks can be utilized to process signals in 6G networks in an energy-efficient, robust, and low-latency matter. Another focus is the topic of resource allocation. We are investigating how wireless networks can use Artificial Intelligence to automatically adapt to changing conditions and requirements in order to dynamically distribute the available bandwidth and anticipate any problems. One machine learning method that is particularly in our focus is federated learning. This refers to the decentralized training of neural networks directly on the end device. In order to open up this learning process for 6G, we are designing a federated learning simulation. 

One central promise that the 6G standard aims to fulfill is real-time capability with extremely low latencies of under 100 μs. However, 6G can only play this card if the reliability of data flow is fully ensured, since any failed transmission would increase latency again. Especially mission-critical applications cannot afford outages or delays, as this would lead to significant production losses or safety risks. The challenge for mobile communications lies in dealing with so-called “blockages“, which are physical obstacles that reflect or weaken signals, thereby severely impairing transmission quality.

Real-time and reliability come as a package deal with us. The focus is on industrial halls: we research technologies to enable reliable real-time radio even amidst metal walls and shadowing zones for mobile participants. This includes fast dynamic rerouting: if an obstacle is detected, the network can set up an automatic detour and send the data traffic via an alternative path. Another focus of our work is on sub-networks in robots and machines. With “UWIN“ we are developing a radio solution that specializes in delay-free and stable communication within such small, local networks. Additionally, we are working on making Time-Sensitive Networking universally usable for 6G. Through prioritization and coordination, it is guaranteed that critical information always arrives at the right place at the right time. 

5G has paved the way for connected mobility, now 6G is set to enable its ultimate breakthrough. The focus is on the transformation of vehicles into intelligent communication centers capable of making data-driven decisions. To this end, vehicles detect traffic dynamics, replicate these in the form of virtual twins, and initiate a continuous exchange of information with other traffic elements. The extremely low latencies of 6G enable the coordination of traffic participants in real time, so that immediate responses can be made to sudden, unpredictable situations. This improves traffic safety and flow.

An essential component of this V2X connectivity is the sidelink technology, which creates the prerequisite for direct communication between vehicles. We are researching how to implement sidelink in higher frequency ranges and will further develop the underlying concepts at the same time. One option is to link it with the joint communication and sensing approach. Here, we are investigating to what extent the capture of sensor data and the dissemination of the information derived from it can be combined in the same radio channel. In addition, we are working on optimizing vehicle communication using Artificial Intelligence. Such a smart sidelink relies on local learning processes in the vehicle, which reduce the data volume and strengthen data protection.