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Course unit, curriculum year 2023–2024

Digital Communication, 5 cr

Tampere University
Teaching periods
Active in period 3 (1.1.2024–3.3.2024)
Active in period 4 (4.3.2024–31.5.2024)
Course code
Language of instruction
Academic years
2021–2022, 2022–2023, 2023–2024
Level of study
Intermediate studies
Grading scale
General scale, 0-5
Persons responsible
Responsible teacher:
Markku Renfors
Responsible teacher:
Mikko Valkama
Responsible teacher:
Simona Lohan
Responsible organisation
Faculty of Information Technology and Communication Sciences 100 %
Coordinating organisation
Electrical Engineering Studies 100 %
Core content
  • Synchronization basics
    - concepts of time, phase and frequency synchronization in digital communications receivers
    -some basic algorithms to acquire synch
  • Information Theoretic Foundation of Electical Communication:
    - Information, entropy, and mutual information;
    - Maximal mutual information and channel capacity;
    - Source coding vs. channel coding.
    - Capacity of frequency-selective and fading channels
  • Baseband and Bandpass Digital Communication:
    - Bits, symbols, and waveforms;
    - Baseband pulse amplitude modulation (PAM), Nyquist pulse-shaping, line coding;
    - Linear I/Q modulation, real and complex symbol alphabets;
    - Digital frequency modulation techniques.
  • Performance of Digital Communication Chains:
    - Effects of additive noise, symbol & bit errors and their probability, Gray mapping;
    - Spectral efficiency and related concepts, connections to channel capacity theorem.
    - Effects of fading on the symbol and bit errors
  • Detection Theory and Intersymbol Interference (ISI) Mitigation:
    - Basics of statistical decision making and detection, maximum likelihood (ML) and maximum a posteriori (MAP) principles;
    - Signal space concepts and connection to practical waveforms, sufficient statistics;
    - Detection of single symbols, matched filtering (MF);
    - Detection of symbol sequences;
    - Optimal receiver front-end, signal space arguments, intersymbol interference (ISI);
    - Zero-forcing (ZF), mean-squared error (MSE) and other optimization principles;
    - ML sequence detection and Viterbi algorithm;
    - Channel equalization, linear vs. nonlinear equalizers, adaptive techniques.
  • Error Control Coding in Digital Communication Systems:
    - Error detection vs. correction vs. prevention, redundancy;
    - Hard and soft decoding, coding gain;
    - Block codes and convolutional codes,
    Viterbi decoding;
    - Coded modulation and trellis codes;
    - Interleaving, puncturing.
    - Basic ideas and application of Turbo codes, LDPC codes and Polar codes.
Complementary knowledge
  • - Basics of partial response (PR) signaling
    - Scrambling
    - Carrier and symbol timing recovery (synchronization)
  • - Various adaptive filtering algorithms and their relative performance; convergence properties and other essential characteristics
Learning outcomes
Compulsory prerequisites
Further information
Learning material
Studies that include this course
Completion option 1
Mandatory requirements: Exam or two midterm exams and Matlab project. It is also possible to pass the course (with grade 1) without taking the exam, by actively attending the learning events and completing the project work.
Completion of all options is required.


29.04.2024 12.05.2024
Active in period 4 (4.3.2024–31.5.2024)

Participation in teaching

10.01.2024 29.05.2024
Active in period 3 (1.1.2024–3.3.2024)
Active in period 4 (4.3.2024–31.5.2024)