Recently, there have been many attempts to apply Machine Learning (ML)-based prediction
mechanisms In wireless networks. One open question is how reliable such predictions can …

The evolution of wireless communications into 6G and beyond is expected to rely on new
machine learning (ML)-based capabilities. These can enable proactive decisions and …

The capability to provide guarantees for network metrics, such as latency, data rate, and
reliability will be an important factor for widespread adoption of next generation mobile …

The number of always-online vehicles continuously increases, and these vehicles will form
an immense mobile sensor network. For example, cars can upload live temperature and …

Next-generation networks are envisioned to be empowered by artificial intelligence with
predictive capabilities. Predicting handovers in high mobility scenarios enables networks …

This article presents two wireless measurement campaigns in industrial testbeds: industrial
vehicle-to-vehicle (iV2V) and industrial vehicle-to-in-frastructure plus sensor (iV21+), with …

As cellular networks evolve towards the 6th generation, machine learning is seen as a key
enabling technology to improve the capabilities of the network. Machine learning provides a …

Quality of service (QoS) estimation is a key enabler in wireless networks. This has been
facilitated by the increasing capabilities of machine learning (ML). However, ML algorithms …

The role of fast yet reliable wireless communications in various application domains is
getting ever more important. At the same time, as use cases are becoming more and more …

Reliable wireless communications play an important role in the automotive industry as it
helps to enhance current use cases and enable new ones such as connected autonomous …