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Learning target / Competences
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understanding the structure and basic mechanisms in digital communication systems
having the capability to design,implement and optimize digital communication systems for different applications
understanding basic digital modulation schemes for baseband and passband transmission
achieving the competence to design and analyse error-protection coding schemes
being used in modern digital communication systems under different constrainsbeing capable to evaluate the performance of digital communication systems
having the capability to model and simulate digital communication systems by using MATLAB/Simulink in combination with the communication blockset.
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Lectures
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Advanced Channel Coding
| Type |
Lecture |
| Nr. |
EMI406 |
| Hours per week |
2.0 |
| Content |
Introduction
Coding; Types of Coding; Modelling of noisy Digital Communication Channels; Coding Gain
Information Theoretical Analysis of a Communication Link
Digital Communication System Model; Information Measures; Entropy and Redundancy, Equivocation, Irrelevance and Transinformation of a Communication Link; Channel Capacity; Examples
Error Protection Coding (FEC)
• General error protection strategies, Types and Capabilities of Linear Codes; Boundaries of Linear Codes
• Mechanisation of Coding and Decoding of linear Block Codes
• Special linear block codes: Hamming Codes, Simplex Codes, Reed-Muller Codes, cyclic block codes, Reed-Solomon (RS) Codes; Bose-Chaudhuri-Hocquenghem (BCH) Codes
• Error Protection Coding for burst error channels: CRC-Codes, Fire-Codes, Interleaving
• Convolutional Coding: Description of convolutional Codes (Tree-, State- and Trellis-Diagram); Characteristics of convolutional Codes (minimum free distance, catastrophic error propagation etc.); ML-Decoding Principle (hard/soft decision Viterbi decoding); puncturing
Advanced Error Protection Coding
• Concatenated Coding:
serial concatenated coding (Product Codes)
parallel concatenated Coding (Turbo Codes)
• Low-density parity-check codes (LDPC - Gallager-Codes)
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| Literature |
J. G. Proakis: Digital Communications. McGraw-Hill, New York, 2007.
D. Declercq et al.: Channel Coding: Theory, Algorithms, and Applications:
Academic Press, 2014.
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Digital Communications with Lab
| Type |
Lecture |
| Nr. |
EMI404 |
| Hours per week |
3.0 |
| Content |
1. Introduction - Review
1.1 General block diagram of a digital communication system
1.2 Characterisation of signals and systems
1.2.1 Periodic signals
1.2.2 Transient signals
1.2.3 Random signals and noise
1.3 LTI - system characterisation
2. Basics of Digital Communications
2.1 Pulse Code Modulation
2.1.1 Sampling theorems for lowpass and bandpass signals
2.1.2 Quantization, coding and SNR calculations
2.2 Pulse shaping for optimum transmission
2.2.1 Inter - Symbol - Interference (ISI)
2.2.2 Nyquist criteria
2.2.3 Raised cosine rolloff filtering
2.3 Filtering for Optimum Detection (Matched Filter, Correlation)
3. Baseband Transmission and Line Coding
3.1 Binary and Multilevel Signaling
3.2 Line Codes and Spectra (NRZ, RZ, Manchester, CMI, AMI, HDBn,MMS42 etc.)
3.2.1 General Requirements on Line codes
3.2.2 Line Codes and Applications (Manchester, CMI, AMI, HDBn,4B3T etc.)
3.2.3 Power Spectra and Spectral Efficiency of Binary Line Codes
4. Bandpass modulation of carrier signals
4.1 Digital bandpass modulations overview
4.2 Phase constellation diagram
4.3 Digital Quadrature Modulator and Demodulator Implementation Structures
4.4 Analysis of exemplary digital carrier modulation schemes
5. Digital communication system analysis and simulation
5.1 Eye pattern diagram
5.2 Bit-error-rate calculation
5.3 Simulation and optimization of digital communication systems using MATLAB/SIMULINK/Communication Toolbox
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| Literature |
A. Glover, P.M. Grant: Digital Communications. Prentice Hall, London, 1997.
L. W. Couch II: Digital and Analog Communication Systems. Prentice Hall,
London, 2012.
J. G. Proakis: Digital Communications. McGraw-Hill, New York, 2007. |
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