activity
20152026
most citedDeep Learning-Based Communication Over the Air

887 citations · 1.4k across the 37 of their papers we have counts for

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Showing 2018Show all

7 papers · 1 filter

cs.IT2018

Near-Capacity Detection and Decoding: Code Design for Dynamic User Loads in Gaussian Multiple Access Channels

Xiaojie Wang, Sebastian Cammerer, Stephan ten Brink

This paper considers the forward error correction (FEC) code design for approaching the capacity of a dynamic multiple access channel (MAC) where both the number of users and their…

cs.IT2018

Avoiding Burst-like Error Patterns in Windowed Decoding of Spatially Coupled LDPC Codes

Kevin Klaiber, Sebastian Cammerer, Laurent Schmalen +1

In this work, we analyze efficient window shift schemes for windowed decoding of spatially coupled low-density parity-check (SC-LDPC) codes, which is known to yield close-tooptimal…

cs.IT2018

Online Label Recovery for Deep Learning-based Communication through Error Correcting Codes

Stefan Schibisch, Sebastian Cammerer, Sebastian Dörner +2

We demonstrate that error correcting codes (ECCs) can be used to construct a labeled data set for finetuning of "trainable" communication systems without sacrificing resources for…

cs.IT2018★ 161 cited

Belief Propagation List Decoding of Polar Codes

Ahmed Elkelesh, Moustafa Ebada, Sebastian Cammerer +1

We propose a belief propagation list (BPL) decoder with comparable performance to the successive cancellation list (SCL) decoder of polar codes, which already achieves the maximum…

eess.SP2018★ 3 cited

On Deep Learning-based Massive MIMO Indoor User Localization

Maximilian Arnold, Sebastian Dörner, Sebastian Cammerer +1

We examine the usability of deep neural networks for multiple-input multiple-output (MIMO) user positioning solely based on the orthogonal frequency division multiplex (OFDM) compl…

cs.IT2018

OFDM-Autoencoder for End-to-End Learning of Communications Systems

Alexander Felix, Sebastian Cammerer, Sebastian Dörner +2

We extend the idea of end-to-end learning of communications systems through deep neural network (NN)-based autoencoders to orthogonal frequency division multiplexing (OFDM) with cy…

cs.IT2018

Belief Propagation Decoding of Polar Codes on Permuted Factor Graphs

Ahmed Elkelesh, Moustafa Ebada, Sebastian Cammerer +1

We show that the performance of iterative belief propagation (BP) decoding of polar codes can be enhanced by decoding over different carefully chosen factor graph realizations. Wit…