Introduction to MATLAB and discussion of most important commands, simulation of a simple transmission chain, channel coding (convolutional codes), coding gain, channels with multipath propagation, models of fading channels and performance for binary transmission, Orthogonal Frequency-Division Multiplexing (OFDM), interleaving, implementation of an OFDM modem.

Medium access control (MAC) protocols in wireless communications system (seminar)

-Introduction to Digital Communications Lab "DCI Lab"

Sampling theorem (sampling and reconstruction), digital modulation techniques, Amplitude Shift Keying (ASK), Binary Phase Shift Keying (BPSK), Frequency Shift Keying (FSK), signal constellation for M-QAM and M-PSK, noisy channel model, signal detection and Bit Error Rate (BER) measurement and eye pattern for noisy channel.

-Digital Communication Through Band-limited Channels Lab "DCIII Lab"

Carrier phase estimation using phase looked loop (PLL) and Costas loop, bit clock regeneration, communication through band-limited channels (Inter Symbol Interference (ISI), Bit Error Rate (BER) measurement and eye pattern, pulse shaping, linear equalizers), Orthogonal Frequency Division Multiplexing (OFDM)(DFT, IDFT, cyclic prefix, PAPR, channel equalization).

 Elements of hypothesis testing; mean-squared estimation covering the principle of orthogonality, normal equations, Wiener filters, related efficient numerical methods like

Levinson-Durbin recursion, Kalman filters, adaptive filters; classification methods based on linear discriminants, kernel methods, support vector machines; maximumlikelihood parameter estimation, Cramer-Rao bound, EM algorithm.

Carrier and timing recovery, signalling in band-limited channels, transmission over linear band-limited channels, intersymbol interference, adaptive equalization, multicarrier transmission and OFDM system.

Introduction, mathematical models for communication channels, linear systems, basics of probability and random variables, the central limit theorem, Fourier transforms, Shannon Kotelnikov (sampling) theorem, stochastic processes, stationary processes and linear time-invariant systems, complex baseband representation of bandpass signals, orthogonal expansions of signals, linear digital modulation schemes, optimum receivers for the additive white Gaussian noise channel.

  • Signale und Systeme (Vorlesung und Übung): Grundlagenkenntnisse der Analysis
  • Digitale Kommunikation I (Vorlesung und Übung): Grundlagenkenntnisse in: lineare Systeme, Analysis, Wahrscheinlichkeitsrechnung
  • Praktika: Shannon-Kotelnikov (sampling) theorem, analog modulation schemes, linear digital modulation schemes, constellation diagram, eye diagram, optimum receivers for the additive white Gaussian noise channel.