EQ2310 Digital Communications 9.0 credits

Digital kommunikation

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.

  • Education cycle

    Second cycle
  • Main field of study

    Electrical Engineering
  • Grading scale

    A, B, C, D, E, FX, F

Course offerings

Autumn 19 for programme students

Autumn 18 for programme students

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

Recommended prerequisites

EQ1220/EQ1240 Signal theory, or equivalent.


Meddelas på kurshemsida i god tid före kursstart. Tidigare år har följande bok använts: "Fundamentals of digital communications," by Upamanyu Madhow, Cambridge University Press, 2008.


  • LAB1 - Laboration, 0.5, grading scale: P, F
  • PRO1 - Project Assignment, 1.0, grading scale: P, F
  • TEN1 - Examination, 7.5, grading scale: A, B, C, D, E, FX, F

Requirements for final grade

Written examination.
Lab exercise.
Project assignment.

Offered by



Lars Kildehøj (lkra@kth.se)


Lars Kildehøj <lkra@kth.se>

Supplementary information

Replaces 2E1432

Add-on studies

EQ2300 Digital signal processing

EQ2410 Advanced digital communications

EQ2400 Adaptive signal processing

EQ2430/EQ2440 Project course in communications/signal processing 


Course syllabus valid from: Spring 2019.
Examination information valid from: Spring 2019.