Neural Network based Decoding

Betreuer: Matthias Hummert
Art der Arbeit: Projekt (MSc)
Arbeit beendet: 11/2022
Bearbeiter: Gerrit Schoo
Status: abgeschlossen


The decoding of short block length codes is a challenging task and the question naturally arises whether a purely data driven decoder based on neural networks (NN) might be an alternative. There already has been some research ongoing in this direction and first results show that these NN-based decoder can yield good performance for short codes but fail if the number of possible codewords grow too large. This shall be further investigated in this project thesis.


The aim of this thesis is to implement an NN-based decoder for very short block length and further investigate the mentioned results. Therefore investigations about machine learning libraries and literature research needs to be done.


In order to process this thesis, knowledge of Channel Coding 1 and 2, Wireless Communication Technologies and programming skills in Python are essential.

Zuletzt aktualisiert am 07.12.2022 von M. Hummert
AIT ieee GOC tzi ith Fachbereich 1
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