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Biografie
I received my B.Eng. degree from the University of Applied Sciences Konstanz (HTWG) in 2020, and subsequently obtained my M.Sc. degree from the Technical University of Munich (TUM) in 2022.
My Master's thesis focused on achievable information rates for space-division multiplexed short-reach fiber-optic communication systems that employ direct-detection receivers. I conducted this research while visiting the Optical Networks Group (ONG) at University College London (UCL).
I received the 2023 MSCE Academic Award for my master's studies, the 2024 Best Poster Award at the European School on Information Theory (ESIT), and the 2024 Teaching Assistant Award from the faculty student council of Electrical and Computer Engineering jointly with Stefan Ritterhoff for the lecture Nachrichtentechnik.
Forschung
Due to the presence of Kerr nonlinearities, a closed-form expression for the input-output relation of the fiber-optic channel cannot be derived, rendering the channel capacity indeterminate. Digital signal processing techniques, such as digital back-propagation, have been proposed as a means of mitigating nonlinear and linear fiber effects.
However, in wavelength switched networks, where receivers are only able to access their specific channel of interest and not interfering channels, only intra-channel effects, such as self-phase modulation, can be mitigated. As a result, cross-phase modulation remains a significant source of distortion in the received signal.
The nonlinear distortions that remain are typically modeled as correlated phase noise and inter-symbol interference within the channel of interest. My research focuses on developing coding schemes and receivers capable of mitigating these distortions.
Receiver scatter plots of a 16-QAM transmission with interfering channels using QPSK (leftmost plot), 16-QAM (middle plot) and Gaussian modulation (rightmost plot). Especially in the rightmost plot, nonlinear phase noise is clearly visible.
Sampling in High-Dimensional Spaces by Exploiting Model Structure: Rao-Blackwellised Particle Filters
Beschreibung
Field of Research & Contents of the Paper
Many problems in statistics and signal processing require expectations E[f(x)] over a distribution p(x) that we can evaluate but cannot sample from directly. Monte Carlo methods, such as importance sampling, address this, and particle filters extend them to sequential problems, where the state of a dynamic system is estimated recursively from noisy observations.
In high-dimensional state spaces, however, particle filters may require an impractically large number of particles. Often, the model has a structure we can exploit: conditioned on some of the state variables, the rest can be handled analytically, for example, with a Kalman filter. Rao-Blackwellised particle filtering (RBPF) samples only the "hard" part of the state and computes the rest exactly. By the Rao–Blackwell theorem, this cannot increase the variance of the resulting estimates.
A foundational paper on RBPF [1] was published around the same time as many other works that discuss similar principles but use different terms. One can also find an introduction in [2] and further applications in [3]. Generally, there is a wide field of research that explains, studies, or uses RBPF.
This work consists of researching and understanding RBPF and finding a toy example to nicely explain it. The paper should then consist of a motivation that shows an example where particle filtering is inefficient, explain the RBPF using this example, and then discuss the improvements RBPF provides. One can either analyze one of the applications discussed in other papers and reuse their result (a breakdown of the essential pieces of information will be necessary, though) or find their own example and run simulations to get corresponding plots. Both approaches are fine.
[1] A. Doucet, N. de Freitas, K. Murphy, and S. Russell, “Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks,” Proc. 16th Conference on Uncertainty in Artificial Intelligence (UAI), 2000.
[2] A. Doucet, N. de Freitas, and N. Gordon (Eds.), Sequential Monte Carlo Methods in Practice, Springer, 2001.
[3] F. Mustière, M. Boli?, and M. Bouchard, “Rao-Blackwellised Particle Filters: Examples of Applications,” IEEE CCECE 2006, 2006.
Organization of the Supervision
After you have successfully applied for the topic, we will hold a kick-off meeting to discuss all necessary details for the upcoming work. After that, the responsibility for the seminar paper is all on you. You can always contact me to ask questions and request meetings; I am happy to assist you along the way. However, I need you to be proactive.
I can provide comments on your work (e.g., the paper's outline and some paragraphs you have already written) whenever you need them, and guide you as you prepare your paper and presentation. Regarding final drafts, I comment on one complete version of your paper. Ideally, this would mean that you do some work (literature research, the paper's outline, the body, the introduction, and the conclusion), and we discuss your results after every step. Ultimately, you provide me with one final draft, and I will comment on it. The draft must be handed in at least 10 days prior to the paper submission deadline. This method is more successful and instructive than writing a paper a few days before the deadline.
Beware that when I comment on your work, this is not the same as a correction. My comments are suggestions for improving the quality of the work, but I cannot spend the time searching for and correcting every mistake that exists or could be made (this would also not align with the seminar's purpose).
I expect solid research. There should be at least two significant references. Those are papers you know in detail and that majorly impact your work. Of course, they are always accompanied by supporting references.
Voraussetzungen
Basic probability theory and Bayesian inference. Ideally, experience with sampling algorithms and/or Kalman filters.
Underdetermined channel estimation problem in extreme pilot sparsity scenarios by transforming it into a lower-dimensional nonlinear parameter estimation task.
Oversampled LMMSE Filters for Wiener Phase Noise Channels
Beschreibung
The thesis studies the mitigation of Wiener phase noise through LMMSE filtering with oversampling. The tradeoff between oversampling factor, LMMSE filter length and performance is investigated.
The goal of the Master's thesis is to develop a deep learning-based signal detection system for spectral data and compare it to state-of-the-art solutions.
The objective is to provide an interface for a fly-over solution between an FPGA and the QSFP-DD800 Connector.
Betreuer:
Alex Jäger - (Rohde & Schwarz)
Abgeschlossene Abschlussarbeiten
Probabilistic Shaping for MIMO Channels with Seperate Detection. Erasmus internship. Co-supervised with Constantin Runge.
Design and Implementation of a Streaming Architecture for High-Throughput Automotive Networks. Bachelor's thesis. In cooperation with Technica Engineering GmbH.
Successive Interference Cancellation for Multimode Fibers. Master's thesis. Co-supervised with Paolo Carniello.
Turbo Detection and Decoding for Nonlinear Fiber Optic Links. Master's thesis. Co-supervised with Diego Lentner.
Perturbation-Based Solutions of the Nonlinear Schrödinger Equation. Seminar paper.
Turbo Equalization for Optical Fiber and/or Phase Noise Channels with Memory. Seminar paper.
Balanced Information Rates for Successive Interference Cancellation. Master's thesis. Co-supervised with Daniel Plabst.
Constant Composition Distribution Matching. Seminar paper.
Spiral Constellations for Long-Haul Fiber-Optic Links. Bachelor's thesis. Co-supervised with Thomas Wiegart.
Neural Network-Based Compensation Techniques for Nonlinear Distortions in Fibre-Optic Links. Seminar paper.
Publikationen
2026
Alex Jäger, Gerhard Kramer: Feedforward and Iterative Phase Noise Compensation for Channels with Chromatic Dispersion. European Conference on Optical Communications (ECOC), 2026 mehr…
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Alex Jäger, Gerhard Kramer: Feedforward and Iterative Phase Noise Compensation for Intersymbol Interference Channels. 2026 Munich Workshop on Shannon Coding Techniques (MSCT), 2026 mehr…
Alex Jäger, Gerhard Kramer: Feedforward Phase Noise Compensation for Intersymbol Interference Channels. IEEE International Symposium on Information Theory (ISIT), 2026 mehr…
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Saquib Amjad, Bensu Baran-Akin, Paolo Carniello, Juergen W. Czarske, Norbert Hanik, Alex Jäger, Carmen Mas-Machuca, Dennis Pohle, Stefan Rothe, and Maria Samonaki: Chapter 9 - 6G Optical Core Networks. In: Holger Boche, Frank Fitzek, Patrick Seeling, Wolfgang Kellerer (Hrsg.): 6G-life: Unveiling the Future of Technological Sovereignty, Sustainability, and Trustworthiness. Elsevier, 2026 mehr…
2025
Alex Jäger: On Low-Complexity Mitigation of Nonlinear Inter-Channel Distortions in Optical Networks. 43. Sitzung der ITG-Fachgruppe „Angewandte Informationstheorie“, 2025 mehr…
Volltext (mediaTUM)
Alex Jäger: On Mitigating Equalization-Enhanced Phase Noise. 21st Joint Workshop on Communications and Coding (JWCC), 2025 mehr…
Volltext (mediaTUM)
Jäger, A.; Kramer, G.: Information rates of successive interference cancellation for optical fiber. IEEE J. Sel. Areas Commun. 43 (5), 2025, 1484-1497 mehr…
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2024
Alex Jäger: Successive Interference Cancellation for Optical Fiber Using Discrete Constellations. 2024 Munich Workshop on Shannon Coding Techniques (MSCT), 2024 mehr…
Volltext (mediaTUM)
Jäger, A.: A Tutorial on Methods for Message Passing with Continuous Variables. ICE Summer Doctoral Seminar, 2024 mehr…
Jäger, A.: Challenges and Research Trends for Fiber-Optic Communication Systems. CoC Industry Day, 2024 mehr…
Jäger, A.; Kramer, G.: Successive interference cancellation for optical fiber using discrete constellations. European Conference on Optical Communications (ECOC), 2024 mehr…
Volltext (
DOI
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Jäger, A.; Kramer, G.: Successive Interference Cancellation for Optical Fiber Using Discrete Constellations. European School of Information Theory (ESIT), 2024 mehr…
2023
Jäger, A.: Bounding the Capacity of Fiber-Optic Channels. 20th Joint Workshop on Communications and Coding (JWCC), 2023 mehr…
2022
Jäger, A.: Achievable Rates for Space-Division Multiplexed Optical Channels with Direct Detection. 6G-Life Project Work Package Workshop, 2022 mehr…
