5 papers
Signal Restoration and Channel Estimation for Channel Sounding with SDRs
Julian Ahrens, Lia Ahrens, Michael Zentarra +1
In this paper, the task of channel sounding using software defined radios (SDRs) is considered. In contrast to classical channel sounding equipment, SDRs are general purpose device…
A Machine Learning Method for Prediction of Multipath Channels
Julian Ahrens, Lia Ahrens, Hans D. Schotten
In this paper, a machine learning method for predicting the evolution of a mobile communication channel based on a specific type of convolutional neural network is developed and ev…
A Machine-Learning Phase Classification Scheme for Anomaly Detection in Signals with Periodic Characteristics
Lia Ahrens, Julian Ahrens, Hans D. Schotten
In this paper we propose a novel machine-learning method for anomaly detection applicable to data with periodic characteristics where randomly varying period lengths are explicitly…
Time is of the Essence: Machine Learning-based Intrusion Detection in Industrial Time Series Data
Simon Duque Anton, Lia Ahrens, Daniel Fraunholz +1
The Industrial Internet of Things drastically increases connectivity of devices in industrial applications. In addition to the benefits in efficiency, scalability and ease of use,…
An AI-driven Malfunction Detection Concept for NFV Instances in 5G
Julian Ahrens, Mathias Strufe, Lia Ahrens +1
Efficient network management is one of the key challenges of the constantly growing and increasingly complex wide area networks (WAN). The paradigm shift towards virtualized (NFV)…