4 papers · 1 filter
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…
Multiplant Nonlinear System Identification by Block-Structured Multikernel Neural Networks in Applications of Interference Cancellation
Svantje Voit, Gerald Enzner
Problems of linear system identification have closed-form solutions, e.g., using least-squares or maximum-likelihood methods on input-output data. However, already the seemingly si…
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…