Institute for Theoretical Information Technology

Seminar zur Kommunikationstheorie (S3/4)

Termine

Seminartermine

Anmeldeschluss des modularen Anmeldeverfahrens ist am 02.04.2019.

Die Einführungsveranstaltung findet am Donnerstag, den 04.04.2019, um 10:30 Uhr im Raum 333, ICT cubes, Kopernikusstraße 16, statt.

Inhalte

Blind Source Separation

• Requirements: Basic knowledge of mathematics and programming. Fluency in written and spoken English.
• Description: The cocktail party describes the problem of separating a desired signal from the interference and noise caused by other simultaneous active sources. Here we will be applying important data analytics tools such as Independent Component Analysis (ICA), Principle Component Analysis (PCA) to separate audio signals. We also provide the opportunity for real world implementation of the developed solution.

Compressed Sensing using Generative Models

• The paper examines how generative adversarial networks can be used for classical signal processing tasks. In a remarkable result, it is shown how MNIST images can be reconstructed only from 10 samples. This means that MNIST images can be compressed to around 1 percent of the original dimension and that in in a very efficient way. The method significantly outperforms LASSO, a well known reconstruction method with established theoretical guarantees.

Improving information security via full-duplex jamming receivers

• Requirements: Being familiar with the basics of wireless communication systems, system modeling. Being familiar with (or interested in) the basics of mathematical optimization. Interest in learning the new concepts/technologies in the context of wireless communications.
• Abstract: A Full-duplex (FD) transceiver is characterized by the capability to receive and transmit at the same time and frequency. As a result, an FD information receiver has the capability to transmit a jamming signal while receiving useful information, and thereby deteriorating the information reception by a potential eavesdropper. This enhances the physical layer security of the communication system. The aformetioned system concept and optimization will be the focus of this seminar work.

ISTA-Net: Iterative Shrinkage-Thresholding Algorithm Inspired Deep Network for Image Compr. Sensing

• Iterative thresholding algorithms have been used successfully for signal recovery in context of compressed sensing applied for instance to functional magnetic resonance imaging (fMRI) applications and single pixel camera. Although very fast compared to convex-programming approaches, the method can be still enhanced if the thresholding is chosen efficiently tailored to different datasets. In this work a deep thresholding network is constructed combining strength of thresholding algorithms and gradient-based neural networks to construct a fast and efficient recovery method.

Optimal sensor deployment under various conditions

• Requirements: Basic knowledge of wireless sensor networks and communication systems. A very good knowledge of mathematics (in particular, various optimization techniques). A very good knowledge of problem modeling in terms of network parameters.
• Abstract: The sensor deployment strategy has a huge impact on the performance of a wireless sensor network (WSN) as well as its effective lifetime. The topic of sensor placement covers various transmitter and receiver deployments and has been widely studied, where different deployment criteria have been considered for specific applications. The majority of the studies have focused on the issues such as coverage and connectivity, target coverage, reliability, cost, delay, and energy and lifetime, in order to define the objective of the optimization problem which yields the desired sensor positions. Recent studies have taken into account the physical parameters of communications, such as the propagation delay and the angle of arrival, in order to find the optimal solutions. This topic can be studied in both two and three dimensional scenarios. The optimal trajectory design for unmanned aerial vehicles (UAVs) is an application example of the generalization of this topic. Due to the high complexity, most of the formulated optimization problems in this context cannot be tackled by conventional techniques.

Voraussetzungen

Erfolgreiche Teilnahme an mindestens einer Veranstaltung aus dem Angebot des Lehstuhls für Theoretische Informationstechnik. (Entscheidung über Zulassung im Einzelfall)

Lernziele

Der Student lernt selbstständiges, wissenschaftliches Arbeiten anhand eines aktuellen Forschungsthemas des Instituts. In der Regel wird eine aktuelle Literaturarbeit aus der Forschung aufgearbeitet, indem Hintergründe erarbeitet und Lücken geschlossen werden. Es können auch Literaturüberblicke verfasst oder Simulationen umgesetzt und evaluiert werden. Diese Arbeit wird in einem wissenschaftlichen Bericht beschrieben und in einem Vortrag unter Nutzung angemessener, moderner Kommunikationsmittel den anderen Seminaristen sowie weiteren Interessierten verständlich vermittelt.

Prüfungen

Leistungsnachweis nach erfolgreicher Teilnahme (schriftliche Ausarbeitung eines Themas und Präsentation).

Einführungsveranstaltung

In dieser Veranstaltung werden die Voraussetzungen geprüft, die Themenverteilung der Seminaristen bestätigt und eine allgemeine Einführung in den Ablauf und die Anforderungen des Seminars gegeben.

Sprechstunden

Dr. Michael Reyer nach Vereinbarung

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