Network Engineering

• Information of the course: lectures, seminars, labs; evaluation and bibliography: pdf
• Course notes (compilation): pdf
• Mid-term exam. Group 1: 22/2/2023 | Group 2: 21/2/2023
• Final exam: 20/3/2024

Sessions

• Lecture 1 - Introduction & Motivation of the course (slides): pdf
• Lecture 2 - Background on stochastic processes (slides): pdf
• Lecture 3 - Markov chains: DTMCs (slides): pdf | CTMCs (slides): pdf 
• Lecture 4 - Markov chains: DTMCs (slides): pdf | CTMCs (slides): pdf 
• Lecture 5 - Introduction to Wi-Fi (pdf, pdf, Example3.zip)
• Lecture 6 - Modelling a network interface 1 (M/M/S/K) : Slides: pdf
• Lecture 7 - Modelling a network interface 2 (M/M/1/K & M/M/1) : Slides: pdf | Example: Modelling a Wi-Fi AP with Donwlink Traffic (pdf)
• Lecture 8 - Multiple hops / End to end delay : Slides: pdf
• Lecture 9 - Mid-term exam
• Lecture 10 - M/G/1 : Slides: pdf | Slides: Packet retransmissions due to errors: pdf
• Lecture 11 - M/G/1 : Multiple traffic flows + Traffic differentiation: pdf
• Lecture 12 - Low-latency region of a M/G/1 queue: pdf

• Seminar 1 - Exercises: pdf
• Seminar 2 - Exercises: pdf
• Seminar 3 - Exercises: pdf
• Seminar 4 - Exercises: pdf
• Seminar 5 - Exercises: pdf

• Lab 1 - Introduction to COST [link] - Basic Communication system [link]
• Lab 2 - Wi-Fi DCF in saturation conditions (Colab env. [link] | |sim, zip)
• Lab 3 - Simulation of queueing systems: M/M/1/K, M/D/1/K, D/M/1/K, etc. [link]
• Lab 4 - Modelling a Wi-Fi Access Point (only Downlink): [link]
• Lab 5 - Project: Traffic-differentiation in a Wi-Fi Access Point (only Downlink) [link]
• Lab 6 - Project: Traffic-differentiation in a Wi-Fi Access Point (only Downlink) [link]

Old Lectures

• Lecture - Call Admission Control in Cellular Networks: Slides: pdf | Report: pdf

Old Matlab Labs (they are still valid as exercises)

• Lab 1 - Report + Matlab functions: zip
• Lab 2 - Report + Matlab functions: zip
• Lab 3 - M/M/1/K and M/M/1 - Report + Matlab functions: zip
• Lab 4 - WIFI-DL model: Report + Matlab functions: zip
• Lab 5 - M/G/1: Report + Matlab functions: zip
• Lab project (pdf) - To be delivered by the date of the final exam

Lab project

• Lab project 2021/22: Traffic differentiation in Wi-Fi

Solutions

• Seminars (zip)
• Old Matlab Labs (zip)

Exams

• 2019/2020: Mid-term (Group1; Group2); Final-exam (pdf)
• 2020/2021: Mid-term (Group1; Group2); Final-exam (pdf)
• 2021/2022: Mid-term (Group1; Group2); Final-exam (--)

Resources

• Bertsekas & Gallagher: Data Networks (book): link

Machine Learning for Networking

• Lecture 1 - ML to create models from data (pdf, Example1.m)
• Lecture 2 - How does WiFi work (slides 1 pdf, slides 2 pdf, Example2.zip)
• Seminar 1 - Analyzing a (WIFI) dataset (Text(pdf), Slides(pdf), link to dataset)
• Lecture 3 - Modelling WiFi performance I  (pdf, Example3.zip)
• Lecture 4 - Modelling WiFi performance II  (pdf, Example4.zip)
• Lab 1 - AP selection using MABs: Scenario set-up (pdf, zip in the Moodle)
• Seminar 2 - Regression and decision tree models (pdf)
• Lecture 5 - Are we lucky? Random exploration  (pdf, Example5.zip)
• Lecture 6 - Reinforcement Learning: Multi-armed Bandits (pdf, Example6.zip)
• Lecture 7 - Reinforcement Learning: Non-stationarity (pdf, Example7.zip)
• Lab 2 - AP selection using MABs: Hands on (pdf, zip in the Moodle)
• Seminar 3 - Classification models (pdf)
• Lecture 8 - Reinforcement Learning: Contexts, States, MDPs + Q-learning (pdf, Example8.zip, pdf, Example9.zip)
• Lab 3 - AP selection using MABs: design your own MAB!
• Lecture 9 - Lab session (to recover the session from May 18, 2022 (Festa Major))
• Lecture 10 - [Practical Session] Reinforcement Learning: Q-learning II  (pdf, Example10.zip)
• Seminar 4 - Neural Networks
• Lab 4 - Introduction to ThingSpeak (zip in the Moodle)
• Lecture 11 - [Practical Session]  ODS - Fem IoT project + Sampling IoT (pdf ODS, pdf, Example11.zip)
• Seminar 5 - Development of the seminar's project
• Lab 5 - IoT Data collection and prediction using ThingSpeak
• Lecture 12 - Open questions (free session) - Suggested reading: link

• Kulin, M., Kazaz, T., De Poorter, E., & Moerman, I. (2021). A survey on machine learning-based performance improvement of wireless networks: PHY, MAC and network layer. Electronics, 10(3), 318. [link]

• Simeone, Osvaldo. "A very brief introduction to machine learning with applications to communication systems." IEEE Transactions on Cognitive Communications and Networking 4.4 (2018): 648-664. [arxiv link]

• Slivkins, Aleksandrs. "Introduction to multi-armed bandits." arXiv preprint arXiv:1904.07272 (2019). [arxiv link]