Graduate School and Research Center in Digital Sciences

Dirk SLOCK

Dirk SLOCK
Dirk SLOCK
Eurecom - Communication systems 
Professor
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Teaching

  • He has taught speech coding for mobile communications, signal modeling and coding, radio engineering, advanced topics, and currently teaches statistical signal processing and signal processing techniques for wireless and wireline communications.

My courses

  • SP4COM / Spring 2019 - Signal Processing for Communications

    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).

  • SP4COM / Spring 2018 - Signal Processing for Communications

    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).

  • SSP / Fall 2018 - Statistical signal processing

    The proper treatment of modern communication systems requires the modelling of signals as random processes. Often the signal description will involve a number of parameters such as carrier frequency, timing, channel impulse response, noise variance, interference spectrum. The values of these parameters are unknown and need to be estimated for the receiver to be able to proceed.

    Parameters may also occur in the description of other random analysis of communication networks, or in the descriptions of sounds and images, or other data, e.g. geolocation. This course provides an introduction to the basic techniques for estimation of a finite set of parameters, of a signal spectrum or of one complete signal on the basis of a correlated signal (optimal filtering, Wiener and Kalman filtering). The techniques introduced in this course have a proven track record of many decades. They are complementary to the techniques introduced in the EURECOM course Stat. They are useful for other application branches such as machine learning, in the EURECOM courses MALIS and ASI.

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

    Course Policies:  Attendance of Lab session is mandatory (15% of final grade).

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Distinctions

  • Prof. Dirk SLOCK was elected "EURASIP Fellow" in 2015
  • In January 2006, he was elected IEEE FELLOW «for contributions to adaptive filtering and signal processing for wireless communications» 
  • He received one Best Journal Paper Award from the IEEE-SP and one from EURASIP in 1992
  • He is the coauthor of two IEEE Globecom 98 and one IEEE SPAWC 2005, Best Student Paper Awards