Graduate School and Research Center in Digital Sciences


Eurecom - Communication systems 
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  • 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 2018 - Signal Processing for Communications

    • The goal of this course is to cover a number of complements to the treatment of physical layer procedures in a wide variety of modem technologies.
    • The details of the adaptation of a number of basic digital communication techniques to some specific communication problems are elaborated. Such details involve for instance 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, fixed point implementation issues of a number of basic algorithms.
    • The extra systems to be covered include xDSL, gigabit Ethernet, powerline systems and DAB/DVB broadcasting.

  • SSP / Fall 2017 - 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.



  • 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