Course detail

Radiocommunication Signals

FEKT-MPA-ARSAcad. year: 2020/2021

The proposed structure of the subject focuses on the use of selected mathematical techniques in modern communication signal processing and wireless communication theory. The goal is to present students specialized mathematical apparatus, which is essential to understanding the principles of modern wireless communications.

Learning outcomes of the course unit

After completing the course, students should be able to independently solve problems associated with the verification and testing of assumptions and properties about the studied phenomena and data files in the telecommunications field. Furthermore, they should be able to independently solve practical tasks, ie choose and justify an appropriate method and apply it.
The student is able to: (a) quantifying the probability of the event; (b) distinguishing between the random variables and describe their characteristics; (c) to test the hypothesis; (d) analyse and describe measurements; (e) estimating the shape of the spectrum and identify the spectral components; (f) identify and test the presence of a signal in noise; (g) evaluate the classification and construct the ROC curve.

Prerequisites

A student who enrolls in the course should be able to compile a simple program in the Matlab environment and practice mathematical calculation procedures.

Co-requisites

Not applicable.

Recommended optional programme components

Not applicable.

Recommended or required reading

GOPI, E.S. Algorithm Collections for Digital Signal Processing Applications Using Matlab, Springer, 2007. (EN)
KAY, S. Intuitive Probability and Random Processing using MATLAB, Springer 2005. (EN)
KOBAYASHI, H. et al. Probability, random processes, and statistical analysis, Cambridge University Press, 2012. (EN)

Planned learning activities and teaching methods

Teaching methods depend on the type of course unit as specified in the article 7 of BUT Rules for Studies and Examinations. Techning methods include lectures, computer laboratories.

Assesment methods and criteria linked to learning outcomes

Requirements for completion of a course are specified by a regulation issued by the lecturer responsible for the course and updated for every. Test written during semester (30 points), final oral+ writting test exam (70 points).

Language of instruction

English

Work placements

Not applicable.

Course curriculum

1. Introduction to probability theory.
2. One random variable. Complete characterisation.
3. Random vectors.
4. The Central Limit Theorem.
5. Confidence intervals and hypothesis testing.
6. Random processes.
7. Correlation analysis
8. Spectrum estimation techniques.
9. MMSE estimation
10. Classification and ROC curve.
11. Detection of signals hidden in noise.
12. Modelling of signals
13. Filtering of signals

Aims

The aim of the course is to present to students a specialized mathematical-statistical apparatus, which is important for understanding the principles of modern wireless communication.

Specification of controlled education, way of implementation and compensation for absences

Evaluation of activities is specified by a regulation, which is issued by the lecturer responsible for the course annually.

Classification of course in study plans

  • Programme MPA-TEC Master's, 1. year of study, winter semester, 4 credits, compulsory

Type of course unit

 

Lecture

26 hours, optionally

Teacher / Lecturer

Exercise in computer lab

13 hours, compulsory

Teacher / Lecturer

eLearning