Font size
  • A-
  • A
  • A+
Site color
  • R
  • A
  • A
  • A
EURECOM
  • Log in
Skip to main content

Technical Spring 2022

  1. Home
  2. Courses
  3. Technical Spring 2022
  • 1 Page 1
  • 2 Page 2
  • » Next page
[WiSec] Wireless Security (FRANCILLON, Aurélien)
Aurelien FrancillonPierre AyoubRomain Cayre
Technical Spring 2022

[WiSec] Wireless Security (FRANCILLON, Aurélien)

Wireless communications are pervasive and have been used for a century. They are used in a very large set of  security applications (communications by security forces, car key remote, alarm system, access control, drone command and control, surveillance devices) . However, day to day applications also require to be protected for privacy and personal security, such as WiFi or mobile communications (2G/3G/4G). At the same a number of challenges are present in wireless communications security, for example, messages are broadcasted, making it possible to intercept them without being noticed. Wireless signals are subject to jamming, making them unavailable.

This course will give a large perspective of the fundamental challenges in securing wireless communications, from the physical layer, modulations to the application protocols. A special focus will be put on practice with hands on exercises (using software defined radios and WiFi dongles).

Teaching and Learning Methods : Course is composed of lectures, Labs and small projects with final presentation.

Course Policies : Class attendance, labs and projects mandatory.

[WebSem] Semantic Web and Information Extraction technologies (TRONCY, Raphaël)
Raphael Troncy
Technical Spring 2022

[WebSem] Semantic Web and Information Extraction technologies (TRONCY, Raphaël)

The Semantic Web is an evolving extension of the World Wide Web in which the semantics of information and services on the web is defined. It derives from W3C director Sir Tim Berners-Lee's vision of the Web as a universal medium for data, information, and knowledge exchange. This course is a guided tour for a number of W3C recommendations allowing to represent (RDF/S, SKOS, OWL) and query (SPARQL) knowledge on the web as well as the underlying logical formalisms of these languages, their syntax and semantics. We will present the problems of modeling ontologies and reconciling data on the web. Finally, we will explain how to extract knowledge from textual documents using natural language processing and information extraction technologies.

Teaching and Learning Methods:Lectures and Lab sessions (group of 2 students max)

Course Policies:Attendance to Lab session is mandatory.

[TraffEEc] Emission and Traffic  Efficiency (HÄRRI, Jérôme)
Jerome Haerri
Technical Spring 2022

[TraffEEc] Emission and Traffic Efficiency (HÄRRI, Jérôme)

This module addresses mechanisms and strategies to improve traffic efficiency and carbon footprint. The objectives are first to introduce the underlying theory such as Waldrop Equilibrium required for efficient path planning. Second, it describes concepts and theory behind the optimization of traffic lights to traffic conditions. Third, it provides guidelines and methodologies to model emissions and integrate them into efficient path planning.  Finally, it trains on best practices to apply these concepts for efficient and green path planning on vehicular traffic simulators.

Teaching and Learning Methods : Lectures and Lab sessions (group of 2 students)

Course Policies : Attendance to Lab session is mandatory

[Speech] Speech and audio processing (EVANS, Nicholas)
Nicholas Evans
Technical Spring 2022

[Speech] Speech and audio processing (EVANS, Nicholas)

This course provides an introduction to the automatic processing of speech and audio signals.  It starts with a treatment of the human speech production and perception mechanisms and looks at how our understanding of them has influenced attempts to process speech and audio signals automatically.  The course then considers the analysis, coding and parameterisation of signals in the case of different speech and audio processing tasks.  After an introduction to essential pattern recognition techniques, the course considers specific applications including speech recognition, speaker recognition and speaker diarization.  The course also includes a treatment of speech and audio coding, noise compensation and speech enhancement.

Teaching and Learning Methods:

The course is comprised of lectures and exercises and laboratory sessions.

Course policies: Attendance of laboratory sessions is mandatory.

[SP4COM] Signal Processing for Communications (SLOCK, Dirk)
Dirk Slock
Technical Spring 2022

[SP4COM] Signal Processing for Communications (SLOCK, Dirk)

The subtitle of this course could be “Multi-Antenna Interference Handling for Multi-User Multi-Cell Systems”. Indeed the main focus is on the exploitation of multiple antennas to (more easily) handle inter-symbol and inter-user interference. Key concepts here are beamforming, MIMO (Multi-Input Multi-Output), Multi-User MIMO, Massive MIMO.

After a basic course in digital communications, a wide range of issues arise in the treatment of physical layer procedures in a wide variety of transmission technologies such as xDSL, gigabit Ethernet, powerline systems, DAB/DVB broadcasting and optical communication systems to name a few. These issues involve e.g. multi-rate echo cancellation for full duplex operation on twisted pair telephone lines, synchronization and equalization techniques in a variety of single and multi-carrier systems, impulsive noise in powerline and automotive systems etc. Even just wireless communications encompass a wide range of systems such as satellite, underwater, near-field communications, fixed wireless access, private systems, sensors, IoT, etc. and a wide range of aspects such as relaying, full duplex radio, cognitive radio, location estimation etc.

Whereas these systems will be briefly mentioned, the main focus will be on cellular wireless and the use of multiple antennas at receivers and transmitters. Spatial filtering, spatiotemporal filtering, and multiuser detection for CDMA are all treated in a unified fashion.

Teaching and Learning Methods: Lectures, Exercise and  Lab session (groups of 1-2 students depending on size of class).

Course Policies: Attendance of Lab session is mandatory (25% of final grade).

[Radio] Radio engineering (KALTENBERGER, Florian)
Florian Kaltenberger
Technical Spring 2022

[Radio] Radio engineering (KALTENBERGER, Florian)

This course treats the subject of modern radio engineering and includes typical RF architectures and their characterizations, modeling, prediction and simulation of radio-wave propagation, cellular planning, systems-level aspects of modern radio network design.

 Teaching and Learning Methods : Lectures and Lab sessions (group of 2 students)

 Course Policies : Attendance to Lab session is mandatory.

[ProtIOT] Iot Communication Protocols (KSENTINI, Adlen)
Adlen Ksentini
Technical Spring 2022

[ProtIOT] Iot Communication Protocols (KSENTINI, Adlen)

This course covers the Low Power Wide Area Network (LPWAN) protocols dedicated to IOT. LPWAN is a technology that intends to offer Internet connectivity to a large number of objects   ("Things") under very strict requirements in terms of cost, power consumption, long distance, battery life, indoor penetration, etc. This course presents two families of LPWA protocols specially developed for IOT: (i) LPWAN for unlicensed spectrum (e.g. LoRa, SigFox ...) and (ii) Cellular LPWAN for licensed spectrum (e.g. 3GPP LTE Cat. M1 or Cat. NB).

Teaching and Learning Methods: The course is organized in 4 lectures and 3 labs.

Course Policies: Labs are Mandatory (attendance + reports)

[PlanTP] Transportation Planning (HÄRRI, Jérôme)
Jerome Haerri
Technical Spring 2022

[PlanTP] Transportation Planning (HÄRRI, Jérôme)

This module addresses mechanisms and strategies to model multi-modal transportation. The objectives are first to introduce concepts of population modeling. Second, it extends graph theory concepts for modeling heterogeneous transportation networks, in particular public transport networks. Mechanisms for activity and demand modeling for multimodal transportation will also be discussed. Finally, this lecture trains on best practices to apply these concepts for efficient multimodal transportation planning on vehicular traffic simulator

Teaching and Learning Methods : Lectures and Lab sessions (group of 2 students)

Course Policies :  Attendance to Lab session is mandatory.

[NetSoft] Network Softwerization (KSENTINI, Adlen)
Adlen Ksentini
Technical Spring 2022

[NetSoft] Network Softwerization (KSENTINI, Adlen)

The architectures of networks and service delivery platforms are subject to an unprecedented techno-economic transformation. This trend, often referred to as Network Softwarization, will yield significant benefits in terms of reducing expenditure and operational costs of next generation networks. The key enablers are Network Function Virtualization (NFV), Software-Defined Networking (SDN), Cloud Computing (mainly Edge Computing).

This course will cover the principle of Network Softwerization by introducing and detailing the concepts of SDN, NFV and Cloud Computing (focusing on the IaaS model and Edge Computing). Besides covering the theoretical aspects, the course will provide an overview of the enabling technologies, and how combining these concepts will allow building flexible and dynamic virtual networks tailored to services, e.g. Anything as a Service (AaaS) and Network Slicing. 

Teaching and Learning methods:

-          Be able to control a network using a NoS (SDN controller)

-          Be able to deploy a virtual network architecture

[MobWat] Wireless Access Technologies (HÄRRI, Jérôme)
Jerome Haerri
Technical Spring 2022

[MobWat] Wireless Access Technologies (HÄRRI, Jérôme)

This module addresses the access methods in Wireless Local Access Networks (WLAN). The basic contention and management mechanisms are detailed. Current and emerging standards of WLAN toward 5G are also presented.

Teaching and Learning Methods : Lectures and Lab sessions (group of 2 students)

Course Policies :  Attendance to Lab session is mandatory.

[MobAdv] Mobile Advanced Networks (NIKAEIN, Navid)
Navid Nikaein
Technical Spring 2022

[MobAdv] Mobile Advanced Networks (NIKAEIN, Navid)

Teaching and Learning Methods: Lectures, Homework (2-3), and a case study (study and present a research paper in a group of 2-3 students). 

Course Policies: Mandatory participation, Case study optional, but recommended.

[MALCOM] Machine Learning for Communication systems (KOUNTOURIS, Marios)
Marios Kountouris
Technical Spring 2022

[MALCOM] Machine Learning for Communication systems (KOUNTOURIS, Marios)

This course introduces fundamental concepts in machine learning (ML), with particular emphasis on communication-efficient distributed learning and applications to networked systems. After a brief introduction to ML methods and deep neural networks (adapted to enrolled students’ prior knowledge), we present key aspects for their efficient application to communication systems. We will cover applications that span different layers and system configurations, including physical layer (signaling, detection), multiple access and radio resource management. We then focus on large-scale distributed and decentralized learning in wireless networks, in particular under constraints (completion time, radio resources, computational efficiency, etc.). We also cover reinforcement learning and theoretical ML topics (generalization, approximation, fairness). Finally, we highlight key challenges in realizing the promise of machine learning for communication networks.

Teaching and Learning Methods: Lectures, exercise sessions, lab sessions, and potentially homework assignments including both problem solving and programming of learned methods. Each session starts summarizing key concepts from previous lecture. Part of each lecture is dedicated to illustrative examples and exercises.

Course Policies: Attendance to lab session is mandatory. Attendance to lectures and exercise sessions is highly recommended.

[HWSec] Hardware Security (PACALET, Renaud)
Renaud Pacalet
Technical Spring 2022

[HWSec] Hardware Security (PACALET, Renaud)

This course offers a survey of several well-known attacks targeting specific weaknesses of hardware (microprocessors, dedicated hardware cryptographic accelerators...) For each of them the conditions of success are explained and some countermeasures are proposed.

Teaching and Learning Methods : Lectures, lab sessions 

Course Policies : Attendance to the lab sessions is mandatory

[FormalMet] FormalMethods-Formal specification and verification of systems (AMEUR, Rabea)
Rabea Ameur
Technical Spring 2022

[FormalMet] FormalMethods-Formal specification and verification of systems (AMEUR, Rabea)

The aims of the course are to provide students with tools that can help to design error-free software/hardware systems. The course  gives both the theoretical foundations and the pratical use of formal methods.

Teaching and Learning Methods : Lectures and Lab sessions.

Course Policies : Attendance to Lab session is mandatory.

[Forensics] Cyber-crime and Computer Forensics (BALZAROTTI, Davide)
Davide Balzarotti
Technical Spring 2022

[Forensics] Cyber-crime and Computer Forensics (BALZAROTTI, Davide)

 

The course is roughly divided in two separate parts. The first covers the   topics of computer forensics and incident response. In particular, we   discuss a number of techniques and open source tools to acquire and   analyze network traces, hard disk images, Windows and Linux operating   system artifacts, log files, and memory images.

The second part of the course deals with the analysis of malware and   unknown binaries. Here the goal is to introduce students to the main  classes of techniques used in malware analysis and reverse engineering.   We cover both static techniques (ELF and PE file structures,   dissasseblers and decompilers, data and control flow analysis, abstract   interpretation, ...) and dynamic techniques (sandboxing, library and   syscall traces, dynamic instrumentation, debugging, taint analysis,   unpacking,...). We will use mostly open source tools, with the exception of IDA Pro.

Teaching and Learning Methods :  Lectures and Homework Assignment

[DigitalSystems] Digital systems, hardware - software integration (PACALET, Renaud)
Renaud Pacalet
Technical Spring 2022

[DigitalSystems] Digital systems, hardware - software integration (PACALET, Renaud)

This course provides an overview of software and hardware design for smart objects. It shows how to specify, design and validate digital hardware components, how to integrate them in a microprocessor-based system, and how to drive them from the software layers.

Teaching and Learning Methods: Lectures, team-work, lab sessions. Students are provided with prototyping boards and design tools for the whole semester duration.

Course Policies: Attendance to the lab sessions is mandatory

[DeepLearning] Deep Learning (MICHIARDI, Pietro)
Pietro Michiardi
Technical Spring 2022

[DeepLearning] Deep Learning (MICHIARDI, Pietro)


Deep Learning is a new approach in Machine Learning which allows to build models that have shown superior performance for a wide range of applications, in particular Computer Vision and Natural Language Processing. Thanks to the joint availability of large data corpus and affordable processing power, Deep Learning has revived the field of Artificial Neural Networks and provoked the renaissance of AI (Artificial Intelligence). The objective of this course is to provide an overview of the field of Deep Learning, starting from simple architectures and pursuing with contemporary and state of the art practices and models. The course is organized as a combination of lectures where the theory is exposed and discussed, and hands-on online tutorials where students can learn technical details of model implementation, training and testing.


[CompMeth] Computational Methods for digital communications (KNOPP, Raymond)
Raymond Knopp
Technical Spring 2022

[CompMeth] Computational Methods for digital communications (KNOPP, Raymond)

Computational methods in digital communications provides a selection of hands-on experiments in programming and implementation techniques for high-performance computing applied to telecommunications. Students will learn architecture concepts and how to optimize software to implement different types of algorithms efficiently on software-based systems.

Teaching methods: The course is primarily given in a lab setting leveraging guided personal work. The instructor gives some lecture material progressively during the course of the lab-sessions in an on-demand fashion. The mini-project teamwork includes regular 45 minutes review meetings with the instructor and teaching assistants to overview progress on the subject.

Grading: 50% final mini-project work and presentation, 50% grading of lab sessions.

[ASI] Advanced Statistical Inference  (FILIPPONE, Maurizio)
Maurizio Filippone
Technical Spring 2022

[ASI] Advanced Statistical Inference (FILIPPONE, Maurizio)

This course focuses on the principles of learning from data and quantification of uncertainty, by complementing and enriching the Introduction to Statistical Learning course. In particular, the course is divided into two main parts that correspond to the supervised and unsupervised learning paradigms. The presentation of the material follows a common thread based on the probabilistic data modeling approach, so that many classical algorithms, such as least squares and k-means, can be seen as special cases of inference problems for more general probabilistic models. Taking a probabilistic view also allows the course to derive inference algorithms for a class of nonparametric models that have close connections with neural networks and support vector machines. Similarly to the Introduction to Statistical Learning course, the focus is not on the algorithmic background of the methods, but rather on their mathematical and statistical foundations. This advanced course is complemented by lab sessions to guide students through the design and validation of the methods developed duringthe lectures.

Teaching and Learning Methods : Lectures and Lab sessions (preferably one student per group)

Course Policies : Attendance of Lab sessions is mandatory

[APPIOT] Iot Application Protocols (KSENTINI, Adlen)
Adlen KsentiniKarim BoutibaMohamed Mekki
Technical Spring 2022

[APPIOT] Iot Application Protocols (KSENTINI, Adlen)

This course covers the application-level protocols dedicated to IOT. Knowing the limited capacity, in terms of battery and CPU, of the things, the classical application protocols used in the Internet like HTTP are not adequate. This course presents the recent application protocols specially developed for IOT. These protocols are organized into two categories: (i) Client/server (like COAP) and (ii) Publish/Subscribe (like MQTT, XMPP). In addition to these protocols, this course introduces two types of architecture, specifically dedicated to host IOT services, like 3GPP MTC and oneM2M.

Teaching and Learning Methods: The course is organised in lectures and labs.

Course Policies: Labs are Mandatory (attendance + reports)

  • 1 Page 1
  • 2 Page 2
  • » Next page

Stay in touch

www.eurecom.fr

  • https://www.eurecom.fr
  • +33 (0)4 93 00 81 00
  • webmaster at eurecom.fr
Data retention summary
Get the mobile app

Proudly made with

Moodle logo

Made with by conecti.me