EQ2310 Digital Communications 9.0 credits
Digital systems provide larger flexibility and better accuracy at a lower cost, compared to analogue systems. For this reason, they are used in most technical areas, including telecommunications, automatic control, audio, image processing, medical and military applications. The course provides a solid background to all these applications.
Educational levelSecond cycle
Academic level (A-D)D
Grade scaleA, B, C, D, E, FX, F
Autumn 16 P1 (8.5 credits), P2 (0.5 credits)
2016 week: 35
2017 week: 3
Language of instruction
Number of lectures
Number of exercises
Form of study
Number of places *
10 - 150
*) The Course date may be cancelled if number of admitted are less than minimum of places. If there are more applicants than number of places selection will be made.
P1: F1, I1, C2, D2. (more info)
Open to all master students
Part of programme
- Master's Programme, Embedded Systems, 120 credits, year 1, INEL, Recommended
- Master's Programme, Embedded Systems, 120 credits, year 1, INPF, Conditionally Elective
- Master's Programme, ICT Innovation, 120 credits, year 2, DMTE, Conditionally Elective
- Master's Programme, Systems, Control and Robotics, 120 credits, year 1, Recommended
- Master's Programme, Systems, Control and Robotics, 120 credits, year 2, Recommended
- Master's Programme, Wireless Systems, 120 credits, year 1, Mandatory
Intended learning outcomes
The student is required to show the following skills to pass the course:
- Identify and describe different techniques in modern digital communications, in particular in source coding, modulation and detection, carrier modulation, and channel coding.
- Carry out, analyze and report simple hardware-based experiments.
- Develop simple software, for example using Matlab, and use this software to simulate and analyze problems within the field, as well as report the development and results.
- Describe and motivate the fact that the implementation and development of modern communication technology requires mathematical modeling and problem solving.
- Apply mathematical modeling to problems in digital communications, and explain how this is used to analyze and synthesize methods and algorithms within the field.
- Formulate a mathematical model which is applicable and relevant in the case of a given problem.
- Use a mathematical model to solve a given engineering problem in the field, and analyze the result and its validity.
To acquire a higher grade, the student is in addition required to show the following skills:
- Identify and describe different techniques in modern digital communications, compare different techniques and judge the applicability of different techniques in different situations.
- Formulate advanced mathematical models which are applicable and relevant in the case of a given problem. When explicit assumptions are missing, the student should be able to judge and compare different possibilities and make own relevant assumptions.
- Use a mathematical model to solve a given demanding engineering problem in the field, and analyze the result and its validity.
Course main content
The course gives a broad introduction to the principles of digital communications. Problem solving based on mathematical modeling is an important part.
Information Theory and Source Coding: Introduction to information theory, entropy, the source coding theorem, quantization, waveform coding (PCM/DPCM/ADPCM, delta-modulation).
Signal Detection: Vector representation of signals, the Gaussian channel (AWGN), optimal receivers, error probability, matched filters, ML and MAP.
Baseband Systems: Signal spectrum. Binary and non-binary modulation. Bit and symbol rate.
Carrier Modulation: ASK, FSK, PSK, QAM. Coherent and non-coherent modulation, CPM, MSK. Symbol and bit-error probabilities. Spectrum and bandwidth.
Channel Coding: Abstract channel models, mutual information, channel capacity, the channel coding theorem. Linear block codes, cyclic codes, convolutional codes. Coding gain, hard and soft decisions. The Viterbi algorithm.
For single course students: 120 credits and documented proficiency in English B or equivalent
EQ1220/EQ1240 Signal theory, or equivalent.
This will be announced well ahead on the course homepage. Previously the following book has been used: "Fundamentals of digital communications," by Upamanyu Madhow, Cambridge University Press, 2008.
- LAB1 - Laboration, 0.5, grade scale: P, F
- PRO1 - Project Assignment, 1.0, grade scale: P, F
- TEN1 - Examination, 7.5, grade scale: A, B, C, D, E, FX, F
Requirements for final grade
Lars Kildehøj (email@example.com)
Lars Kildehøj <firstname.lastname@example.org>
Ragnar Thobaben <email@example.com>
EQ2300 Digital signal processing
EQ2410 Advanced digital communications
EQ2400 Adaptive signal processing
EQ2430/EQ2440 Project course in communications/signal processing
Course syllabus valid from: Autumn 07.
Examination information valid from: Autumn 07.