Paper Info
Title
Online Label Recovery for Deep Learning-based Communication through Error Correcting Codes.
Abstract
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 the transmission of known symbols. This enables adaptive systems, which can be trained on-the-fly to compensate for slow fluctuations in channel conditions or varying hardware impairments. We examine the influence of corrupted training data and show that it is crucial to train based on correct labels. The proposed method can be applied to fully end-to-end trained communication systems (autoencoders) as well as systems with only some trainable components. This is exemplified by extending a conventional OFDM system with a trainable pre-equalizer neural network (NN) that can be optimized at run time.
Year
DOI
Venue
2018
10.1109/iswcs.2018.8491189
ISWCS
DocType
Volume
Citations 
Conference
abs/1807.00747
2
PageRank 
References 
Authors
0.37
0
5
Name
Order
Citations
PageRank
Stefan Schibisch120.37
sebastian cammerer215716.76
Sebastian Dörner3283.92
Jakob Hoydis42121112.59
Stephan ten Brink52912204.86