M.Sc. Francesca Diedolo
Technische Universität München
Lehrstuhl für Nachrichtentechnik (Prof. Kramer)
Postadresse
Postal:
Theresienstr. 90
80333 München
Biografie
- Seit Februar 2021 wissenschaftliche Mitarbeiterin am Lehrstuhl für Nachrichtentechnik der TUM
- M.Sc. in Communications Engineering an der TUM, 2018-2020
- B.Sc. in Elektro- und Informationstechnik an der Università degli Studi di Padova, 2015-2018
Lehre
Machine Learning for Communications (WS 2122)
Abschlussarbeiten
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Laufende Abschlussarbeiten
Geometric and Probabilistic Constellation Shaping via end-to-end Learning
Beschreibung
Voraussetzungen
Information Theory
Coded Modulation
Machine Learning
Betreuer:
Geometric and Probabilistic Constellation Shaping via end-to-end Learning
Beschreibung
When designing constellations, both the locations and probability of occurrence of the points can be optimized. These approaches are referred to as geometric and probabilistic shaping, respectively.
The papers [1], [2], [3] explain how this optimization can be performed with a trainable autoencoder structure.
The seminar consists in understanding and summarizing the history of this topic.
When designing constellations, both the locations and probability of occurrence of the points can be optimized. These approaches are referred to as geometric and probabilistic shaping, respectively.
The papers [1], [2], [3] show how this optimization can be performed with a trainable autoencoder structure.
The seminar consists in understanding and summarizing the history of this topic.
[1] https://arxiv.org/abs/2112.05050
[2] https://ieeexplore.ieee.org/abstract/document/9024567
[3] https://ieeexplore.ieee.org/abstract/document/9348032
Voraussetzungen
Information Theory
Coded Modulation
Machine Learning
Betreuer:
Publikationen
2022
2021
- Label Extension for 32QAM: The Extra Bit for a Better FEC Performance-Complexity Tradeoff. 2020 European Conference on Optical Communications (ECOC), IEEE, 2021 mehr… BibTeX Volltext ( DOI )