3 papers
cs.NI2025
Improving Wi-Fi Network Performance Prediction with Deep Learning Models
Gabriele Formis, Amanda Ericson, Stefan Forsstrom +3
The increasing need for robustness, reliability, and determinism in wireless networks for industrial and mission-critical applications is the driver for the growth of new innovativ…
cs.NI2025
On the Prediction of Wi-Fi Performance through Deep Learning
Gabriele Formis, Amanda Ericson, Stefan Forsstrom +3
Ensuring reliable and predictable communications is one of the main goals in modern industrial systems that rely on Wi-Fi networks, especially in scenarios where continuity of oper…
eess.SY2025
Towards Ultra-Reliable 6G in-X Subnetworks: Dynamic Link Adaptation by Deep Reinforcement Learning
Fateme Salehi, Aamir Mahmood, Sarder Fakhrul Abedin +2
6G networks are composed of subnetworks expected to meet ultra-reliable low-latency communication (URLLC) requirements for mission-critical applications such as industrial control…