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20182025
most citedEnabling FDD Massive MIMO through Deep Learning-based Channel Prediction

45 citations · 140 across the 9 of their papers we have counts for

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cs.IT2021★ 31 cited

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…

cs.IT2021

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…

cs.IT2021

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…

cs.IT2020★ 9 cited

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…

cs.IT2019

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…

cs.IT2019★ 38 cited

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.…

cs.IT2019★ 45 cited

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…

cs.IT2018★ 17 cited

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…

cs.IT2018

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…