Analysis, Modeling and Simulation of Communication Networks
| Vortragende/r (Mitwirkende/r) | |
|---|---|
| Nummer | 0000002179 |
| Art | Vorlesung mit integrierten Übungen |
| Umfang | 4 SWS |
| Semester | Sommersemester 2026 |
| Unterrichtssprache | English |
| Stellung in Studienplänen | Siehe TUMonline |
| Termine | Siehe TUMonline |
- 08.07.2026 08:00-09:30 0406, Seminarraum
- 08.07.2026 09:45-11:15 0406, Seminarraum
- 15.07.2026 08:00-09:30 0406, Seminarraum
- 15.07.2026 09:45-11:15 0406, Seminarraum
Teilnahmekriterien
Beschreibung
Simulation and modelling basics (traffic modelling, link-, system-, packet level simulation, SW/HW in the loop), probability theory fundamentals, random number generation, mobility models, channel models, topology models, graph theory and algorithms, queuing models, discrete event-based simulation, Monte Carlo simulation, rate-based simulation, analysis of simulation results, statistical analysis, visualisation of results, simulation languages and tools, simulation packages;
as part of the course a simulation tool will be stepwise designed by the students during the tutorial and as homework. Simulation results will be analysed by applying fundamental tools from statistics.
as part of the course a simulation tool will be stepwise designed by the students during the tutorial and as homework. Simulation results will be analysed by applying fundamental tools from statistics.
Inhaltliche Voraussetzungen
Basics in communication networks (protocols and performance analysis). The knowledge of following modules are therefore recommended:
- Broadband Communication Networks
Basic knowledge in object-oriented programming and basic knowledge in the Python programming language as well as basic knowledge in C++ are recommended.
- Broadband Communication Networks
Basic knowledge in object-oriented programming and basic knowledge in the Python programming language as well as basic knowledge in C++ are recommended.
Lehr- und Lernmethoden
Learning method:
In addition to the individual methods of the students, consolidated knowledge is aspired by repeated lessons in exercises, practical programming assignments and tutorials.
Teaching method:
During the lectures students are instructed in a teacher-centered style. The exercises and programming assignments are held in a student-centered way.
In addition, students are asked to stepwise design a simulation tool and perform simulation and analysis projects in class and as homework.
In addition to the individual methods of the students, consolidated knowledge is aspired by repeated lessons in exercises, practical programming assignments and tutorials.
Teaching method:
During the lectures students are instructed in a teacher-centered style. The exercises and programming assignments are held in a student-centered way.
In addition, students are asked to stepwise design a simulation tool and perform simulation and analysis projects in class and as homework.