45 citations · 140 across the 9 of their papers we have counts for
10 papers
Integrated Radio Sensing Capabilities for 6G Networks: AI/ML Perspective
Victor Shatov, Steffen Schieler, Charlotte Muth +11
The sixth-generation wireless communications (6G) is often labeled as "connected intelligence". Radio sensing, aligned with machine learning (ML) and artificial intelligence (AI),…
Massive-MIMO Iterative Channel Estimation and Decoding (MICED) in the Uplink
Daniel Verenzuela, Emil Björnson, Xiaojie Wang +2
Massive MIMO uses a large number of antennas to increase the spectral efficiency (SE) through spatial multiplexing of users, which requires accurate channel state information. It i…
Serial vs. Parallel Turbo-Autoencoders and Accelerated Training for Learned Channel Codes
Jannis Clausius, Sebastian Dörner, Sebastian Cammerer +1
Attracted by its scalability towards practical codeword lengths, we revisit the idea of Turbo-autoencoders for end-to-end learning of PHY-Layer communications. For this, we study t…
Wiener Filter versus Recurrent Neural Network-based 2D-Channel Estimation for V2X Communications
Moritz Benedikt Fischer, Sebastian Dörner, Sebastian Cammerer +4
We compare the potential of neural network (NN)-based channel estimation with classical linear minimum mean square error (LMMSE)-based estimators, also known as Wiener filtering. F…
Deep-learning Autoencoder for Coherent and Nonlinear Optical Communication
Tim Uhlemann, Sebastian Cammerer, Alexander Span +2
Motivated by the recent success of end-to-end training of communications in the wireless domain, we strive to adapt the end-to-end-learning idea from the wireless case (i.e., linea…
On Recurrent Neural Networks for Sequence-based Processing in Communications
Daniel Tandler, Sebastian Dörner, Sebastian Cammerer +1
In this work, we analyze the capabilities and practical limitations of neural networks (NNs) for sequence-based signal processing which can be seen as an omnipresent property in al…
Decoder-in-the-Loop: Genetic Optimization-based LDPC Code Design
Ahmed Elkelesh, Moustafa Ebada, Sebastian Cammerer +2
LDPC code design tools typically rely on asymptotic code behavior and are affected by an unavoidable performance degradation due to model imperfections in the short length regime.…
Enabling FDD Massive MIMO through Deep Learning-based Channel Prediction
Maximilian Arnold, Sebastian Dörner, Sebastian Cammerer +3
A major obstacle for widespread deployment of frequency division duplex (FDD)-based Massive multiple-input multiple-output (MIMO) communications is the large signaling overhead for…
Time-Bandwidth Product Perspective for Multi-Soliton Phase Modulation
Alexander Span, Vahid Aref, Henning Buelow +1
Multi-soliton pulses are potential candidates for fiber optical transmission where the information is modulated and recovered in the so-called nonlinear Fourier domain. While this…
Efficient Precoding Scheme for Dual-Polarization Multi-Soliton Spectral Amplitude Modulation
Alexander Span, Vahid Aref, Henning Buelow +1
Spectral amplitude modulation for dual-polarization multi-soliton transmission is considered. We show, that spectral amplitudes become highly correlated during propagation along a…