Software for Communication Systems

Data is displayed for the academic year: 2025./2026.

Lecturers

Assoc. Prof.
Marin Šilić
PhD
Asst. Prof.
Jelena Božek
PhD
Asst. Prof.
Josip Vuković
PhD

Lectures

Filip Turčinović
PhD

Laboratory exercises

Filip Turčinović
PhD

Course Description

The course is focused on understanding the fundamental concepts of digital communications through their practical implementation in the Python programming language. Signals will be generated, basic operations on them (such as convolution, correlation, etc.) will be implemented, and the signals will be analyzed in both the time and frequency domains. The DFT (Discrete Fourier Transform) and FFT (Fast Fourier Transform) algorithms will be implemented. The second part of the course focuses on digital modulation techniques and their implementation. Their performance will be analyzed, and constellation diagrams will be visualized. In the final part of the course, real-world examples will be addressed, including the development of simple software tools for signal processing and transmission in modern communication systems. Throughout the course, the emphasis is on connecting theory with implementation and developing intuitive, applicable knowledge that can be transferred to real-world engineering tasks and projects.

Study Programmes

University graduate
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Elective Courses (2. semester)

Learning Outcomes

  1. Define the basic concepts of communication systems.
  2. Apply various signal processing operations.
  3. Evaluate the advantages and limitations of frequency-domain signal analysis.
  4. Combine knowledge of signal processing, digital communications, and programming.
  5. Compare different digital signal processing methods in the context of practical communication system applications.

Forms of Teaching

Lectures

The classes are organized in two blocks: The first block comprises 7 classes and a midterm exam, while the second comprises 6 classes and a final exam. this makes in total 15 weeks with 2 hours per week.

Laboratory

Students need to resolve independently practical tasks for laboratory exercises.

Grading Method

Continuous Assessment Exam
Type Threshold Percent of Grade Threshold Percent of Grade
Laboratory Exercises 0 % 30 % 0 % 30 %
Mid Term Exam: Written 0 % 35 % 0 %
Final Exam: Written 0 % 35 %
Exam: Written 0 % 70 %

Week by Week Schedule

  1. Signal generation and operations in Python
  2. Signal sampling and spectral aliasing analysis
  3. Implementation of convolution and correlation
  4. Simulation of LTI system responses
  5. Implementation of DFT and signal spectrum analysis
  6. Analysis of the Fast Fourier Transform (FFT) algorithm implementation
  7. Application of FFT in signal processing operations
  8. Midterm exam
  9. Implementation of digital modulation schemes
  10. Simulation of a digital modulator model
  11. Performance analysis of modulation techniques
  12. Case study: software tools for communication systems
  13. Case study: software tools for communication systems
  14. Case study: software tools for communication systems
  15. Final exam

Literature

Brian McFee (2023.), Digital Signals Theory, CRC Press
Allen B. Downey (2016.), Think DSP, "O'Reilly Media, Inc."

General

ID 222729
  Summer semester
5 ECTS
L1 e-Learning
30 Lectures
0 Seminar
0 Exercises
26 Laboratory exercises
0 Project laboratory
0 Physical education excercises

Grading System

88 Excellent
75 Very Good
63 Good
50 Sufficient

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