Course detail
Analysis of Radiocommunication Signals
FEKT-NSTKAcad. year: 2018/2019
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 with master's degree program Electronics and Communication Engineering specialized mathematical apparatus, which is essential to understanding the principles of modern wireless communications.
Language of instruction
Number of ECTS credits
Mode of study
Guarantor
Department
Learning outcomes of the course unit
The student is able to:
- Quantifying the probability of the event
- Distinguishing between the random variables and describe their characteristics
- To test the hypothesis by parametric and non-parametric way
- Describe the probability density by Gaussian mixture models
- Estimating the shape of the spectrum and identify the spectral components
- Identify and test the presence of a signal in noise
Prerequisites
- To compose a simple program in Matlab
- Practicing a mathematical calculation procedures
Co-requisites
Planned learning activities and teaching methods
Assesment methods and criteria linked to learning outcomes
Course curriculum
2. The definition and the type of random variables, the characteristics of random variables, an entropy.
3. Multinomial random variables.
4. Functions of continuous random variables.
5. The central limit theorem and the law of large numbers.
6. Introduction to the theory of statistics, point and interval estimation, confidence intervals
7. Hypothesis testing, the parametric and the nonparametric approach.
8. Gaussian mixed models.
9. Random processes (stationarity, ergodicity of stationary processes, energy spectrum, Gaussian process).
10. Transformation of random processes.
11. Orthogonal transformation, Karhunen-Loev transformation, PCA.
12. Spectrum estimation techniques (parametric and nonparametric methods).
13. Detection of hidden signals in noises
Work placements
Aims
Specification of controlled education, way of implementation and compensation for absences
Recommended optional programme components
Prerequisites and corequisites
Basic literature
LEVIN, B.: Teorie náhodných procesů a její aplikace v radiotechnice, SNTL Praha (CS)
Recommended reading
GOPI, E., S.: Algorithm Collections for Digital Signal Processing Applications Using Matlab, Springer, 2007, 190 pp., ISBN 978-1-4020-6409-8 (EN)
KOBAYASHI, H. et al: Probability, random processes, and statistical analysis, Cambridge University Press, 2012, 780 pp., ISBN 978-0-521-89544-6 (EN)
STEHLÍKOVÁ, B. a kol.: Metodologie výzkumu a statistická inference. 9. vyd. Brno: Folia univ. agric. et silvic. Mendel. Brun., 2009. II. ISBN 978-80-7375-362-7. (CS)
Classification of course in study plans