Picture of Francesca Diedolo

M.Sc. Francesca Diedolo

Technical University of Munich

Chair of Communications Engineering (Prof. Kramer)

Postal address

Postal:
Theresienstr. 90
80333 München

Biography

  • Doctoral researcher at the Chair of Communications Engineering at TUM since February 2021
  • M.Sc. in Communications Engineering at TUM, 2018-2020
  • B.Sc. in Electrical Engineering and Information Technology at Università degli Studi di Padova, 2015-2018

Available Theses

Neural Networks (NNs) for Direct Detection

Description

In [1] we consider a short-reach fiber-optic link with a single photodiode at the receiver, which is a so-called direct detector (DD). The DD outputs a signal, propotional to the squared magnitude of its input. At first glance, this makes phase modulation challgenging. In [1] we showed that inter-symbol intereference (ISI) can be used to retrieve the phase. A suboptimal symbol-wise MAP detector was then proposed for phase retrieval. However, the detector exhibits a large complexity, which grows exponentially in the amount of ISI.

The task of the student is to efficiently approximate the MAP detector using a NN.  An appropriate NN type/structure needs to be selected. Finally, lower bounds on the achievable rates are computed to evaluate the performance of the NN and compare it to the MAP detector [1].

[1] D. Plabst et al., "Achievable Rates for Short-Reach Fiber-Optic Channels With Direct Detection," in Journal of Lightwave Technology, vol. 40, no. 12, pp. 3602-3613, 15 June15, 2022, doi: 10.1109/JLT.2022.3149574.

 

 

Prerequisites

Machine Learning

Statistical Signal Processing

Supervisor:

Factor Graphs and the Sum-Product Algorithm

Description

 

This paper [1] introduces factor graphs and describes the sum-product algorithm, which is a generic message-passing algorithm operating in factor graphs. The algorithm computes various marginal functions associated with the global function.  

This algorithm is very powerful, in fact, a surprisingly wide variety of algorithms developed in the artificial intelligence, signal processing, and digital communications communities can be seen as specific instances of the sum-product algorithm, operating in an appropriately chosen factor graph. Some examples are the forward/backward algorithm, the Viterbi algorithm, Pearl’s belief propagation algorithm, the iterative turbo decoding algorithm, the Kalman filter, and even certain FFT algorithms.

The task of the student is to learn and understand factor graphs and the sum-product algorithm. The student can then relate and analyze other known algorithm under the framework of the sum-product algorithm.

[1] https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=910572

Prerequisites

Information Theory

Supervisor:

Theses in Progress

Publications

2022

  • Diedolo, F.; Böcherer, G.; Schädler M.; Calabrò S.: Nonlinear Equalization for Optical Communications Based on Entropy-Regularized Mean Square Error. European Conference on Optical Communication (ECOC), 2022 more… BibTeX

2021

  • Böcherer, G.; Diedolo, F.; Pittala, F.: Label Extension for 32QAM: The Extra Bit for a Better FEC Performance-Complexity Tradeoff. 2020 European Conference on Optical Communications (ECOC), IEEE, 2021 more… BibTeX Full text ( DOI )