Dependable vehicular wireless communication links under harsh propagation conditions are of prime importance for future intelligent transportation systems (ITS). Such intelligent transportation systems will provide services like collision avoidance, wrong way driver warning, intelligent routing, enable e-mobility or the efficient operation of highspeed railway systems.

Vehicular wireless communications is characterized by highly time-variant and non-stationary wave propagation conditions. In this course we will discuss channel characterization method as well as signal processing algorithms for channel estimation and data detection in vehicular wireless communications. We exemplify the theory by discussing the design of practical vehicular communication standards.

In this course we will cover the fundamentals of linear-time variant systems to characterize wireless communication channels under strong time-variance and in non-stationary environments. We discuss the measurement of such non-stationary fading processes based on channel-sounding and their characterization and emulation with graded complexity form ray-tracing to tap delay line models.

For the transceiver design we focus on systems based on orthogonal frequency division multiplexing (IEEE 802.11p and LTE-A) and discuss advanced iterative channel estimation methods from the classical Wiener filter to two-dimensional adaptive subspace models.

To exploit the diversity in vehicular channels we introduce the concept of channel prediction as basis for antenna selection, coded cooperation and interference alignment for mobile users. Here we introduce the basic concepts as well as the complexity caused by the time-variant fading process.

The course will be based on the books "Wireless Communications" by A. F. Molisch and "Wireless Communications Over Rapidly Time-Varying Channels" Ed. F. Hlawatsch and G. Matz as well as recent research results. Lecture notes are available as collection of slides.

First class: Wed., 13.3.2012, 4 - 5.30 p.m., Semraum_389 (CG0402, 4. floor)

Written exam at the end of the lecture.

4 small MATLAB assignments throughout the semester.

Basic knowledge in wireless wave propagation and estimation theory is helpfull.