After successful completion of the course, students are able to: (1) know and understand fundamental digital modulation and detection techniques, especially regarding their properties, advantages, and limitations; (2) solve relevant problems.

1. Introduction:  Outline, basic facts, communication channels, historic perspective, related courses, literature

2. Pulse amplitude modulation (PAM) fundamentals:  Baseband PAM, passband PAM (including spread spectrum modulation and CDMA), transmit spectrum, spectral efficiency, symbol alphabet design, problems

3. Elementary passband PAM systems:  Channel, elementary receiver, equivalent discrete-time baseband system, intersymbol interference, Nyquist pulses, eye diagrams, symbol and bit error probability, matched filter, problems

4. Equalization:  Linear equalizer (zero-forcing design, mean-square-error design, adaptive equalizer, fractionally spaced equalizer), decision-feedback equalizer, problems

5. Optimum sequence detectors:  MAP and ML sequence detectors, probability of a sequence error, signal design, incoherent ML sequence detector, problems

6. ML sequence detectors for passband PAM:  Spectral factorization, whitened matched filter, trellis diagram, Viterbi algorithm, problems

7. Multipulse modulation and detection techniques:  Orthogonal multipulse modulation (transmit spectrum, spectral efficiency, FSK, MSK, ML sequence detector, matched filterbank, generalized Nyquist criterion, error probability, incoherent ML sequence detector), orthogonal multipulse PAM (transmit spectrum, spectral efficiency, ML sequence detector, multicarrier modulation, DMT, OFDM), problems

8. Channel capacity:  Basic example, capacity of the AWGN channel, the promise of channel capacity, basic facts of channel coding (threshold SNR, coding gain, bandwidth expansion), problems

9. Block-based coded transmission:  HISO channel, Gaussian memoryless channel, HIHO channel, discrete memoryless channel, binary symmetric channel, optimum soft-input and hard-input block decoding (MAP, ML), optimum block decoding for the Gaussian memoryless channel and the discrete memoryless channel, problems

The prof (Hlawatsch) verbally presents the class material, discusses the material with his students, and answers the students' questions. For this, he uses a blackboard, on which he writes certain characters and draws simple figures with of a piece of chalk (also using different colors if helpful). He also uses a tablecloth to erase the board every now and then. Finally, he uses an overhead projector to project more complicated figures and tables on a screen. The prof's presentation is supported by detailed lecture notes. In the exercise section, students present and explain relevant exercise problems to the audience; in addition, they have to hand in their own solutions of "mandatory problems" to the teaching assistant before the respective exercise unit. Students are required to personally participate in the exercise units.

First class: Friday, March 3, 2023 from 10:45 to 12:00 in lecture room EI 2.
Second class: Tuesday, March 7, 2023 from 15:15 to 16:30 in lecture room EI 3.

Exercise section: There will be 6-8 exercise units per semester taking place at the lecture’s scheduled time and place. The dates of the exercise units will be announced in TISS at least one week in advance. Attendance of the exercise units is mandatory (one no-show allowed).

At the beginning of each exercise unit, the solutions for two mandatory problems have to be handed in. By presenting solutions on the blackboard, students can earn up to 20 credits during the entire semester. The number of credits earned for a presentation depends on the difficulty of the problem and the quality of the presentation and solution. A collection of possible exercise problems can be found in the lecture notes. The specific problems (including the mandatory problems) for each exercise unit will be announced in TISS at least one week in advance.

Admittance to the written exam:

In order to be admitted to the written exam, the following conditions must be fulfilled:  

– At least 10 credits have been earned by presenting problems to the class.

– All mandatory problems have been handed in (2 incomplete mandatory problems and 1 “no-show” are permitted).

Written exam:

At the written exam, which consists of 4 problems, up to 80 credits can be earned. A calculator and a collection of mathematical formulas are permitted to be used in the exam. Lecture notes will be provided by the exam supervisors. To check for dates and register for an exam use TISS.

Admittance to the oral exam:

To be admitted to the oral exam, at least 40 credits must be earned at the written exam. Under this condition, the credits of the written exam are added to those of the exercise units, and an intermediate grade is obtained as follows:

The final grade depends on the intermediate grade and the oral exam.

Exam consists of written and oral parts.

Previous exam problems are available (please check with the assistant directing the exercises)

Lecture notes for this course are available at Grafisches Zentrum der TU Wien, Wiedner Hauptstraße 8-10, 1040 Vienna. For complementary literature see the lecture notes.

A sound knowledge of signals and systems, random variables, and random processes is an absolute prerequisite