Abstract

The interest in the multidimensional structure of the mobile radio channel is growing rapidly. This is mainly due to the fact that the future beyond 3G wireless systems will employ multi-antenna transceivers in order to improve spectral efficiency and radio link quality. Consequently, realistic channel models that are verified by real-world measurement campaigns are needed especially for transceiver design and network planning purposes.

Channel sounding and related propagation parameter estimation are key tasks in creating such channel models. In particular, the double-directional modeling of the radio channel has attracted a lot of interest because it gives a better physical insight into the wave propagation mechanism in real radio environments and it has the ability to remove the measurement antenna influence from the channel observation. Moreover, studying and comparing the performance of various MIMO (multiple-input-multiple-output) transceiver structures requires such advanced channel models as well.

In this talk we address the problem of parametric channel estimation in channel sounding. The propagation between transmitter and receiver is not only carried by specular-alike propagation paths but also by diffuse scattering. In this work we develop a stochastic ML method for estimating the propagation parameters. The model provides significant benefits over deterministic modeling both from the computational point of view as well as statistical optimality. The propose method attains the CRB with relatively small sample sizes. It also allows for modeling arbitrary clusters of scatterers by employing a mixture distribution model in angular domain.

Biography

Visa Koivunen (Senior Member, IEEE) received his D.Sc. (Tech) degree with honors from the University of Oulu, Dept. of Electrical Engineering. From 1992 to 1995 he was a visiting researcher at the University of Pennsylvania, Philadelphia, USA.   In 1996 he held a faculty position at the Department   of Electrical Engineering, University of Oulu.  From August 1997 to August 1999 he was an Associate Professor at the Signal Processing Labroratory, Tampere University of Technology.   Since 1999, he has been a Professor of Signal Processing at the Department of Electrical and Communications Engineering, Helsinki University of Technology (HUT), Finland. He is one of the Principal Investigators in SMARAD Center of Excellence in Radio and Communications Engineering nominated by the Academy of Finland.  Since 2003, he has also been an adjunct professor at the University of Pennsylvania, Philadelphia, USA.

Dr. Koivunen's research interests include statistical, communications and sensor array signal processing. He has published more than 170 papers in international scientific conferences and journals. He received the best paper award in IEEE PIMRC 2005. He has served as an associate editor for IEEE Signal Processing Letters.  He is a member of the editorial board for the Signal Processing Journal. He is also a member of the IEEE Signal Processing for Communication Technical Committee (SPCOM-TC).