Performance Analysis in Telecommunications Systems

Objectives

This course introduces the main methodologies of performance analysis in telecommunications networks. Several theoretical reference models are taught, which are explored in the theoretical-practical classes through the accomplishment of several exercises. The exercises allow a deeper understanding of the use of theoretical models in practical scenarios, allowing the students to select the different modeling techniques according to their suitability. The teaching of theoretical models is complemented with the adoption of different numerical computation tools, as well as the use of network simulators, which allow the specification of operational scenarios for performance measurement. Decision-making is encouraged and evaluated during the semester. Given the set of performance modeling techniques, students can choose the approaches that best fit the practical scenarios, thus stimulating a critical approach regarding the different tools studied in the course.

General characterization

Code

12724

Credits

6.0

Responsible teacher

Luís Filipe Lourenço Bernardo, Paulo da Costa Luís da Fonseca Pinto

Hours

Weekly - 4

Total - 53

Teaching language

Português

Prerequisites

- Knowledge about the organization of telecommunication systems;

- No pre-requisites related to previous courses 

Bibliography

Performance Analysis of Computer Networks

Authors: Sadiku, Matthew N.O., Musa, Sarhan M.

Springer, 2013


Network Performance Analysis

Author(s): Thomas Bonald Mathieu Feuillet

Willey, 2011


Performance Analysis of Communications Networks and Systems

Author: Piet Van Mieghem, Technische Universiteit Delft, The Netherlands

Cambridge, 2006


Teaching method

- Theoretical classes providing theoretical background and practical examples

- Laboratory classes to practice simulation exercises and interpretation of the performance results

Evaluation method

- Written works to be assigned during the semester (70%);

- Report of the LAB activities/exercises (30%);

Subject matter

- Introduction

       - Random Variables

       - Basic Distributions

       - Correlation

       - Inequalities and Limit Laws


- Processes 

       - Poisson Process

       - Renewal Theory

       - Discrete-time Markov Chains

       - Continuous-time Markov Chains

       - Geometric Branching Process

       - Queueing Models


- Physics of Networks

       - Circuit Traffic

       - Real-time Traffic

       - Elastic Traffic

       - Network Performance


- Holistic Assessment

       - Physical Layer Performance

       - MAC Performance

       - Routing and Transport Performance

       - Upper layers and Cross-layering


Programs

Programs where the course is taught: