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Signal & System Theory Group

Professor Peter Schreier
Universität Paderborn, Germany

Simulation of a Wi-Fi communication system


Wireless local area networks (WLAN) are indispensable in modern communications and have become part of our everyday life. Wi-Fi enables millions of devices to exchange data and to connect to the Internet wirelessly. Thanks to the specification of the IEEE-802.11 standards, devices from different manufacturers can be used in the network. The standards specify different layers of the Wi-Fi system such as the data link, media access control (MAC) or the physical layer (PHY). This project will focus on the physical layer, which includes the underlying wireless communication technologies that define the achievable data rates in the 2.4 or 5 GHz frequency bands.

The goal of the project is to implement an IEEE 802.11 standard with focus on the physical layer. You will take a look into different PHY implementations that include coding and modulation techniques, channel estimation techniques, different frame formats and their detection, etc. You are going to model the transmitter, the wireless channel and the receiver according to the standard. You will also evaluate the performance of the system for simulated and measured channels.

Basic programming experience in Matlab or Python is a must. Knowledge about wireless communications is helpful but not required.

Medical X-ray Simulator


Simulated data can be extremely useful in order to develop and/or test algorithms. Especially in domains where obtaining and annotating data is difficult, simulations can be a way to solve real-world problems. Such a domain is medical image processing. In our group, we develop image processing algorithms that are able to locate bones and other structures in medical X-ray images. For this purpose, we have a simple simulator that can render X-ray images. The simulator uses a database of 3D scans of real bones, which enables us to render 2D projections from different perspectives.

In this project, you would build upon the existing simulator and improve it to make the images more realistic. Examples would be to implement different X-ray and noise models and evaluate them. Another improvement would be to locate the contours in the rendered 2D images and to label the different anatomical parts. Thus you would learn about statistical shape models, image rendering and work on a medical application.

Knowledge of digital signal processing and MATLAB or Python. Knowledge of image processing and C++ is an advantage.