Prof. Mohamed-Slim Alouini has been teaching the following courses within the Electrical Engineering (EE) and Applied Mathematics and Computational Sciences (AMCS) programs of the Computer, Electrical, and Mathematical Sciences and Engineering (CEMSE) division at King Abdullah University of Science and Technology (KAUST):
AMCS 143. Introduction to Probability and Statistics (3-0-0)
This course provides an elementary introduction to probability and statistics with applications. Topics include: basic probability models; combinatorics; random variables; discrete and continuous probability distributions; statistical estimation and testing; confidence intervals; and an introduction to linear regression.
AMCS 241/STAT 250 Probability and Random Processes (3-0-3)
Introduction to probability and random processes. Topics include probability axioms, sigma algebras, random vectors, expectation, probability distributions and densities, Poisson and Wiener processes, stationary processes, autocorrelation, spectral density, effects of filtering, linear least-squares estimation, and convergence of random sequences.
EE 244 Wireless Communications (3-0-3) ⊙ Prerequisite: Preceded or accompanied by EE 241 and EE 242.
This course introduces fundamental technologies for wireless communications. It addresses the following topics: review of modulation techniques, wireless channel modeling, multiple access schemes, cellular communications, diversity techniques, equalization, channel coding, selected advanced topics such as CDMA, OFDM, Multiuser detection, space time coding, smart antenna, and software radio.
EE 355 Estimation, Filtering, and Detection (3-0-3) ⊙ Prerequisite: EE 241.
Principles of estimation, linear filtering, and detection. Estimation: linear and nonlinear minimum mean squared error estimation and other strategies. Linear filtering: Wiener and Kalman filtering. Detection: simple, composite and binary and multiple hypotheses as well as Neyman-Pearson and Bayesian approaches.
EE 390 Advanced Wireless Communication (3-0-3)
This is an advanced course in wireless communication theory, providing a brief review of fundamental concepts in wireless communications followed by in-depth discussions on several topics related to the performance analysis of modern wireless communication systems and networks. It includes advanced topics related to wireless channel modeling, diversity techniques, multiple-input/multiple-output (MIMO) communications, opportunistic communication, cooperative communication, cognitive radio systems, energy harvesting-based communication, and advanced wireless communication systems. It serves as an excellent basis from which to commence research in the performance analysis of wireless communication systems and networks. Various aspects of the course bring students up to date with the very latest developments in this field, as reported in recent publications.