6 citations · 6 across the 3 of their papers we have counts for
4 papers
Cross-Comparison of Neural Architectures and Data Sets for Digital Self-Interference Modeling
Gerald Enzner, Niklas Knaepper, Aleksej Chinaev
Inband full-duplex communication requires accurate modeling and cancellation of self-interference, specifically in the digital domain. Neural networks are presently candidate model…
On Digital Optimization of Analog Self-Interference Cancellation for Full-Duplex Wireless Systems
Niklas Knaepper, Gerald Enzner, Aleksej Chinaev
Wireless systems with inband full-duplex transceiver typically require multiple lines of defense against the effect of harsh self-interference, specifically, to avoid saturation of…
On Neural-Network Representation of Wireless Self-Interference for Inband Full-Duplex Communications
Gerald Enzner, Aleksej Chinaev, Svantje Voit +1
Neural network modeling is a key technology of science and research and a platform for deployment of algorithms to systems. In wireless communications, system modeling plays a pivo…
Control Architecture of the Double-Cross-Correlation Processor for Sampling-Rate-Offset Estimation in Acoustic Sensor Networks
Aleksej Chinaev, Sven Wienand, Gerald Enzner
Distributed hardware of acoustic sensor networks bears inconsistency of local sampling frequencies, which is detrimental to signal processing. Fundamentally, sampling rate offset (…