106 citations · 285 across the 19 of their papers we have counts for
4 papers · 1 filter
QoS prediction in radio vehicular environments via prior user information
Noor Ul Ain, Rodrigo Hernangómez, Alexandros Palaios +2
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 driving…
From Empirical Measurements to Augmented Data Rates: A Machine Learning Approach for MCS Adaptation in Sidelink Communication
Asif Abdullah Rokoni, Daniel Schäufele, Martin Kasparick +1
Due to the lack of a feedback channel in the C-V2X sidelink, finding a suitable modulation and coding scheme (MCS) is a difficult task. However, recent use cases for vehicle-to-eve…
Berlin V2X: A Machine Learning Dataset from Multiple Vehicles and Radio Access Technologies
Rodrigo Hernangómez, Philipp Geuer, Alexandros Palaios +14
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 actions fr…
Transfer Learning in Multi-Agent Reinforcement Learning with Double Q-Networks for Distributed Resource Sharing in V2X Communication
Hammad Zafar, Zoran Utkovski, Martin Kasparick +1
This paper addresses the problem of decentralized spectrum sharing in vehicle-to-everything (V2X) communication networks. The aim is to provide resource-efficient coexistence of ve…