TSKS04 Digital Communication Continuation Course
Course Program Spring 2016
Innehåll 
Separata sidor 

General  General  
Time  Time  
Teachers and Staff  Teachers and Staff  
Course Literature  Course Literature  
Examination  Examination  
Lectures  Lectures  
Tutorials  Tutorials 
1. General
TSKS04 Digital Communication Continuation Course is a course that continues where TSKS01 Digital Communication ends. It is intended to give an indepth description of several important estimation, coding, and decoding issues that arise in realistic digital communication systems, and theoretically founded solutions to these issues.
If you are reading a paper copy of this course program:
There is more information on the course webpage:
//www.commsys.isy.liu.se/TSKS04.
Among other things, this course information is there.
2. Time
The teaching activities consist of lectures, tutorials and laboratory exercises.
There are eleven lectures and nine tutorials.
The laboratory exercises are done in groups of about four to five people in the computer rooms at ISY. There are several scheduled lab sessions. There is no teacher present at these sessions, but can be contacted when needed. We expect these sessions to be well enough for completing the lab tasks.
3. Teachers and Staff
During the spring 2016, the following people are involved in the course.
Lectures and examination: 
Emil Björnson
emil.bjornson@liu.se tel. 286732 

Tutorials and lab exercises: 
<Okänt användarnamn: salka35>
salil.kashyap@liu.se tel. 281000 
Emil and Salil have their offices in Building B, top floor, corridor A between entrances 27 and 29.
4. Course Literature
Course book:
 U. Madhow, Fundamentals of digital communication, Cambridge University Press 2008.
You may also have use of the literature from the courses TSDT14 Signal Theory and TSKS01 Digital Communication, and especially the following:
 Mikael Olofsson: Tables and Formulas for Signal Theory (course material in Signal Theory).
Some additional material will be distributed during the course:
Appendix A: Power Spectral Density of Digital Modulation Schemes
Appendix B: Introduction to Estimation Theory for Communication
5. Examination
The examination consists of two parts; laboratory exercises and a written exam.
5.1 Laboratory exercises (LAB1)
The laboratory exercises are done in groups of about four to five students, and they are examined based on one report that should be handed in to the examiner. Cooperation between groups is encouraged, but no code may be shared and each group should write their own independent report.
The laboratory exercises are based on Matlab and Simulink, the same environment as was used in TSKS01 Digital communication. There are five scheduled sixhour sessions in computer rooms, but the exercises are estimated to correspond to about three such occasions.
The laboratory exercises correspond to 1 ECTS credit (hp), and are graded using the scale Pass/Fail.
5.2 Written Examination (TEN1)
The following aids are allowed at the exam:
 Pocket calculator with empty memory.
 Mikael Olofsson: Tables and Formulas for Signal Theory (course material in Signal Theory).
 U. Madhow, Fundamentals of digital communication, Cambridge University Press 2008.
No notes are allowed on those aids.
The written exam consists of five problems, which each can give you at most five points. You can thus get at most 25 points on the exam. Grade limits:
 Grade 3: 12 points
 Grade 4: 16 points
 Grade 5: 20 points
Grades 3, 4 and 5 are translated to ECTS grades C, B and A.
5.3 Total Grade
When you have passed both parts of the examination (LAB1 och TEN1), the final grade on the course will be the grade from the written exam.
6. Lectures
Please observe that the following schedule should be interpreted as an indication about approximately when different topics are treated. As the course proceeds, this plan may be adjusted.
Lecture n:o  Chapter  Main topic  Part 

1    Introduction  Course plan 
2.1  Introduction  Prerequisites  
2.5.2 and extra material  Power spectral density (PSD)  PSD of linearly modulated random signals  
2  2.2, 2.3  Baseband representation  Complex baseband representation of stochastic processes 
3  4.1 and extra material  Estimation  Introduction to estimation 
4  4.14.3, 4.5.1 and extra material  Estimation for synchronization  Channel estimation, complex Gaussian 
5  3.2, 4.34.5  Estimation for synchronization  Hypothesis testing, delay and phase estimation 
6  4.44.5, 5.15.2  Estimation for equalization  Noncoherent communication, ML sequence estimation 
7  5.4  Estimation for equalization  ML sequence estimation, the Viterbi algorithm 
8  5.55.6  Linear equalization  Suboptimal equalizers, ZF and MMSE 
9  7.1  Error control codes  Convolutional codes, encoding, structure 
10  7.1 and extra material  Error control codes  Noncatastrophic encoders, decoding, Viterbi again 
11  7.1 and extra material  Error control codes  Error probability 
Summary 
7. Tutorials
The tutorials are supposed to be opportunities for discussion about solving problems. Below is a suggestion for problems to treat in each occasion. You should study those problems in advance in order to benefit the most from those tutorials.
Number  Main topic  Part  Problems 

1  Power spectral density (PSD)  Modulated random signals  Extra Tasks (problems 3, 4, 5) 
Baseband representation  Stochastic Processes  2.8, 2.12 (a,b), 2.13  
2  Intro to Laboratory Exercise  Instructions and hints  Lab Memo 
Line codes  Wikipedia article  
Estimation  Basics  Kay: 3.1, 3.3, 3.9, 7.3, 7.12. Extra material: B.1  
3  Estimation for synchronization  Basics, Phase and delay estimation  3.6, 3.8, 4.2, 4.4, 4.11 (4.8) 
4  Estimation for equalization  MLSE  5.1, 5.2, 5.3 
5  Estimation for equalization  MLSE  5.4, 5.6acd, 5.8 
6  Linear equalization  ZF & MMSE  5.10ab, 5.11a, 5.13 
7  Error control codes  Convolutional codes  J&Z: 1.24, 2.1a, 3.2, 3.8c, 3.10, 4.1, 4.2 
8  Error control codes  Convolutional codes  7.1, 7.2, 7.3, 7.4, 7.5b, 7.7 
9  Summary  Exam Problems  TBD 
The problems listed for Tutorial 2 are from Kay, Fundamentals of Statistical Signal Processing: Estimation Theory, Prentice Hall, 1993. Those problems will be distributed at that tutorial.
The problems listed for Tutorial 7 are from Johannesson & Zigangirov, Fundamentals of Convolutional Coding, IEEE Press, 1999. Those problems will be distributed at that tutorial.
Questions about the problems are welcome before the corresponding tutorial. Send them by email to your tutorial teacher <Okänt användarnamn: salka35> . In that way you can help your teacher to plan the tutorials.
Sidansvarig:
Emil Björnson
Senast uppdaterad: 2019 07 30 10:16