Embedded Systems and Signal Processing
Contents
Students learn the principles and concepts of modern signal processing with focus on highly integrated digital transmission systems (e.g. mobile-phones, WLAN). In laboratory exercises methods and concepts covered in the lectures are implemented and tested on hardware (FPGAs, DSPs, μCs) by students.Lectures with courses [VK]
Courses and labs[KU]
Research Seminar and Project
Lectures with courses [VK]
[700.600] Embedded Communications
Semester |
Summer semester |
Allocation in the Curriculum |
Master Curriculum, Information Technology
|
Recommended Semester |
2nd |
Teacher |
Prof. Mario Huemer, Michael Lunglmayr Embedded Systems and Signal Processing Group, Institute of Networked and Embedded Systems Email: Mario.Huemer@aau.at, Michael.Lunglmayr@aau.at |
Type of lecture and number of credits |
VK 2 SWS, 4 ECTS |
Description |
This lecture course deals with the architecture of modern wireless communication systems. All main functional blocks of a mobile phone platform including the baseband processor and the RF (radio frequency) transceiver are addressed. A main focus is on the board level and on the chip level architectures. In the "Digital Baseband Transceiver" chapter important baseband algorithms (equalization, channel estimation, OFDM, MIMO signal processing,...), possible implementation options, and corresponding complexity considerations are discussed. The "Analog Transceiver" chapter deals with the analog signal processing tasks of a wireless device, modern transmitter and receiver architectures are discussed and future trends on the way to Software Defined Radio (SDR) architectures are presented. In parallel a practical course will be offered. Systems and algorithms presented in the lecture will be simulated and tested in the MATLAB/SIMULINK environment. |
Topics |
1. Introductory part (Short review on digital communications) 2. The mobile radio channel 3. Abstract hardware view on a mobile phone terminal platform 4. The digital baseband transceiver 5. Single versus multi carrier techniques (OFDM) 6. Channel estimation, equalization 7. MIMO concepts 8. The analog transceiver 9. Receiver architectures 10. Transmitter architectures |
Keywords |
Mobile phone platforms, mobile radio channel, digital modulation, equalization, channel estimation, OFDM, RF transceivers |
Prior knowledge |
Basics in digital communications |
Learning objective |
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Recommended Literature |
Lecture notes |
Language |
English |
Related Lectures |
Mobile Communications |
Recommended Lectures |
Communications Engineering (Nachrichtentechnik) |
[700.650] Signal Processing Architectures
Semester |
Winter semester |
Allocation in the Curriculum |
Master Curriculum, Information Technology
|
Recommended Semester |
|
Teacher |
Prof. Mario Huemer Embedded Systems and Signal Processing Group, Institute of Networked and Embedded Systems Email: Mario.Huemer@aau.at |
Type of lecture and number of credits |
VK 2 SWS, 4 ECTS |
Description |
This lecture course deals with signal processing algorithms and with appropriate implementation architectures that focus on embedded applications. As a consequence low power consumption and low chip area are of great importance for the regarded architectures. The course starts with a short repetition of important signal processing theory and algorithms (FFT, digital filters). In the following the focus lies on implementation oriented issues like fixed point effects and architecture options for various important signal processing algorithms and applications. In parallel a lab will be offered, which will cover the following:
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Topics |
1. Introduction & review of digital signal processing basics 2. DSP arithmetic 3. DSP hardware: DSPs, FPGAs and ASICs 4. CORDIC-algorithm: theory, architectures and applications 5. Fixed point effects in digital filtering 6. Multirate signal processing (interpolation, decimation, filter banks): theory and low power / low area HW-architectures 7. Low cost digital filters 8. Sigma-delta modulation and oversampling ADCs 9. Numerically controlled oscillators |
Keywords |
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Prior knowledge |
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Learning objective |
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Recommended Literature |
Lecture notes |
Language |
English |
Related Lectures |
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Recommended Lectures |
[700.660] Information Theory and its Applications in Communication Engineering
Semester |
Summer semester |
Allocation in the Curriculum |
Master Curriculum, Information Technology
|
Recommended Semester |
2nd |
Teacher |
Prof. Johannes Huber Embedded Systems and Signal Processing Group, Institute of Networked and Embedded Systems Email: Johannes.Huber@uni-klu.ac.at |
Type of lecture and number of credits |
VK 2 SWS, 4 ECTS |
Description |
The students acquire fundamental insights into information theoretical methods and their application to the assessment and optimization of digital transmission systems. |
Topics |
1. Basic terms and concepts in information theory 2. Channel coding 3. Source coding |
Keywords |
Information, entropy, channel capacity, channel coding, source coding |
Prior knowledge |
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Learning objective |
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Recommended Literature |
Lecture notes; broad literature (incl. textbooks) on information theory; e. g. Cover, Thomas: Elements of Information Theory, Wiley, 2006. |
Language |
English |
Related Lectures |
Embedded Communications, Mobile Communications |
Recommended Lectures |
Nachrichtentechnik (Communications Engineering), Stochastic 1 (Basics in Probability and Random Variables) |
[700.680] Adaptive and Statistical Signal Processing
Semester |
Summer semester |
Allocation in the Curriculum |
Master Curriculum, Information Technology
|
Recommended Semester |
2nd |
Teacher |
Prof. Mario Huemer, Michael Lunglmayr Embedded Systems and Signal Processing Group, Institute of Networked and Embedded Systems Email: Mario.Huemer@aau.at, Michael.Lunglmayr@aau.at |
Type of lecture and number of credits |
VK 2 SWS, 4 ECTS |
Description |
Statistical and adaptive signal processing algorithms can be found at the heart of many electronic systems designed to transmit, receive, store or extract information. These systems include radar, sonar, speech, image analysis, biomedicine, communications, control... and many more. This lecture gives an introduction to the most prominent concepts. We will adopt the theory to a large number of applications from the engineering world (mainly from communications engineering and radar). Algorithms presented in the theory part will be simulated and tested in the MATLAB/SIMULINK environment. |
Topics |
1. Random Variables and Vectors (short review) 2. Classical Estimation in Signal Processing (Bounds, Linear Models, ML, BLUE, LS) 3. Bayesian Estimation in Signal Processing (MMSE, MAP, LMMSE) 4. Discrete Time Stochastic Processes 5. Wiener Filter and their Applications 6. Adaptive Filter (LMS, RLS algorithms) and their Applications |
Keywords |
Parameter estimation, optimum filters, adaptive filters, LS, MMSE, LMMSE |
Prior knowledge |
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Learning objective |
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Recommended Literature |
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Language |
English |
Related Lectures |
Embedded Communications |
Recommended Lectures |
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Courses and Labs [KU]
[700.601] Embedded Communications
Semester |
Summer semester |
Allocation in the Curriculum |
Master Curriculum, Information Technology
|
Recommended Semester |
2nd |
Teacher |
Dipl.-Ing. Alexander Onic Embedded Systems and Signal Processing Group, Institute of Networked and Embedded Systems Email: Alexander.Onic@uni-klu.ac.at |
Type of lecture and number of credits |
KU 2 SWS, 3 ECTS |
Description |
Various concepts of wireless communication systems and algorithms presented in the Embedded Communications lecture will be implemented, simulated and tested in MATLAB. |
Topics |
1. Linear modulation schemes 2. Pulse shaping 3. Matched filtering 4. Multipath propagation 5. Bit error simulations 6. OFDM (Orthogonal Frequency Division Multiplexing) 7. Bit loading for OFDM |
Keywords |
Mobile phone platforms, mobile radio channel, digital modulation, equalization, channel estimation, OFDM, RF transceivers |
Prior knowledge |
Knowledge of MATLAB is mandatory. |
Learning objective |
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Recommended Literature |
Lecture notes |
Language |
English |
Related Lectures |
Mobile Communications |
Recommended Lectures |
Communications Engineering (Nachrichtentechnik) |
[700.651] Signal Processing Architectures Lab
Semester |
Winter semester |
Allocation in the Curriculum |
Master Curriculum, Information Technology
|
Recommended Semester |
|
Teacher |
Dipl.Ing. Christian Lederer, Dr.-Ing. Michael Lunglmayr Embedded Systems and Signal Processing Group, Institute of Networked and Embedded Systems |
Type of lecture and number of credits |
KU 4 SWS, 6 ECTS |
Description |
This lecture course deals with signal processing algorithms and with appropriate implementation architectures that focus on embedded
applications. As a consequence low power consumption and low chip area is of great importance for the regarded architectures. The course
starts with a repetition of important signal processing theory and algorithms (Sampling theorem, DFT, FFT, FIR and IIR-filters).
|
Topics |
1. Characterization of digital signals 2. Sampling and reconstruction, sampling theorem
3. DFT and FFT: theory and implementation architectures
4. Fixed point effects in digital filtering and efficient architectures 5. CORDIC-algorithm: theory, architectures and applications 6. Multirate signal processing (interpolation, decimation) : theory and low power / low area HW-architectures 7. Architectures for digital signal generators (DDS, Polynomial approximation, IIR-implementations, CORDIC) 8. Architectures for digital signal processors 9. FPGAs for signal processing 10. Applications |
Keywords |
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Prior knowledge |
Basic digital signal processing knowledge.
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Learning objective |
The SPA practical course is intended to consolidate fundamentals of the lecture (VK) and practice their use. Most exercises target on the use of Matlab, which is a numeric math software which is broadly used for simulation and verification. After simulation the signal processing algorithms will be implemented in VHDL on an FPGA board. |
Recommended Literature |
Lecture notes |
Language |
English |
Related Lectures |
Signal Processing Architectures |
Recommended Lectures |
Research Seminar and Project
[700.698] Research Seminar on Embedded Systems and Signal Processing
Semester |
Winter semester |
Allocation in the Curriculum |
Master Curriculum, Information Technology
|
Recommended Semester |
|
Teacher |
Prof. Mario Huemer Embedded Systems and Signal Processing Group, Institute of Networked and Embedded Systems Email: Mario.Huemer@aau.at |
Type of lecture and number of credits |
SE 2 SWS, 6 ECTS |
Description |
In this research seminar topical subjects in the area of Embedded Communications and Signal Processing will be regarded. Based on topical scientific publications on a particular subject participants develop a powerpoint presentation and a paper on the selected topic, and finally give a talk for their fellow students and their supervisor. NOTE: The seminar will be held in blocks. Topics will be presented and assigned in the first meeting. Also the semester's schedule will be presented in the first meeting. |
Topics |
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Keywords |
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Prior knowledge |
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Learning objective |
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Recommended Literature |
Scientific Publications |
Language |
English |
Related Lectures |
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Recommended Lectures |
[700.696] Research Project in Embedded Systems and Signal Processing
Semester |
Winter semester |
Allocation in the Curriculum |
Master Curriculum, Information Technology
|
Recommended Semester |
|
Teacher |
Prof. Mario Huemer Embedded Systems and Signal Processing Group, Institute of Networked and Embedded Systems Email: Mario.Huemer@aau.at |
Type of lecture and number of credits |
KU 8 SWS, 12 ECTS |
Description |
Students work independently on a research oriented project. |
Topics |
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Keywords |
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Prior knowledge |
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Learning objective |
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Recommended Literature |
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Language |
English |
Curricula
Curriculum Master
official german version
inofficial english translation
Curriculum Bachelor
official german version
inofficial english translation
Contact
Dr.-Ing. Kyandoghere Kyamakya
Contact
Students Representatives
Website
Research Groups
Control and Measurement Systems
Embedded Systems and Signal Processing