Neural Network based Decoding

Betreuer: Matthias Hummert
Art der Arbeit: Projekt (MSc)
Ausgabe: -
Bearbeiter: -
Status: zu vergeben
Kurzfassung:

Motivation:

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.

Goal:

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.

Requirements:

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 12.04.2021 von M. Hummert
AIT ieee GOC tzi ith Fachbereich 1
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