Future 6G networks could significantly improve the performance of telemedicine and other digital healthcare services by dynamically distributing computing power and data processing across the network. Researchers from the Technical University of Munich (TUM) and TUM University Hospital have demonstrated a new approach that could enable up to 40 percent more medical applications to run simultaneously, even when network and computing resources are limited.
As healthcare increasingly relies on telemedicine, continuous patient monitoring and remote procedures, the ability to transmit and process data reliably and without interruption becomes critical. Delays or disruptions can have serious consequences, particularly for applications such as remote surgery or real-time clinical decision support.
The researchers focused on a key challenge: determining where medical applications should be processed within a future 6G environment. Depending on the situation, computing tasks can be executed close to the patient, within the hospital, at a nearby network node or in a remote data centre.
Most efficient location
Processing data closer to the patient helps minimise latency and improves responsiveness. However, concentrating all workloads at the network edge could quickly overwhelm available resources. The newly developed method dynamically determines the most efficient location for each application based on current network conditions, computing capacity and application requirements.
“For medical applications, it is not enough to transport data from A to B as quickly as possible,” said Wolfgang Kellerer, Professor of Communication Networks at TUM’s School of Computation, Information and Technology and member of TUM-MIRMI. “Future networks will need to decide where computing resources are required, which applications should be prioritised and when functions should be moved within the network. In healthcare, this flexibility can play a crucial role in ensuring the reliable availability of digital services.”
According to simulation results, the approach allows up to 40 percent more medical applications to operate simultaneously compared with conventional resource allocation methods. The findings were presented at the International Federation for Information Processing (IFIP) Networking 2026 Conference in Lugano, Switzerland.
Towards healthcare-ready 6G networks
Expected to emerge around 2030, 6G networks are projected to offer data rates up to 100 to 1,000 times faster than 5G, sub-millisecond latency and AI-driven network management. Unlike previous generations of mobile connectivity, 6G is expected to integrate artificial intelligence directly into the network architecture, enabling autonomous optimisation and real-time resource allocation.
For healthcare, these capabilities could support a new generation of digital services. Potential applications include continuous remote patient monitoring, AI-assisted diagnostics, digital twins for treatment planning and advanced telemedicine services that require ultra-reliable, low-latency communication.
The technology is also expected to support remote robotic surgery, where even the smallest delay in data transmission can affect clinical outcomes. In addition, 6G’s sensing capabilities could allow networks and connected devices to detect movement and environmental changes, opening new possibilities for patient monitoring and preventive care.
While commercial 6G deployment remains several years away, the TUM study highlights how future networks may become a critical foundation for scalable, reliable and digitally supported healthcare delivery.
