Research Areas
Our research activities span from fundamental research in signal processing and information theory to applied research in wireless systems, digital communications, navigation, measurement technology, and real-time implementation.
Multi-antenna Wireless Communication
Next generation wireless systems will use multiple antennas at both the base station and user terminals. The performance of such systems can be improved by using channel information at the transmitters, at the expense of increased control signaling. We have therefore proposed a number of strategies to achieve similar gains with a minimum of feedback and to provide robustness to channel uncertainty. For systems with DFE based receivers, robust precoders have been proposed, that can be based on long-term channel statistics. For systems with (near) ML receivers, a lattice-based precoding approach has been proposed. A combination of long-term channel statistics with heavily quantized information of the channel gain, can be used for both scheduling and spatial processing in multi-user scenarios. A popular alternative is opportunistic beamforming, where we have studied feedback reduction techniques and the optimal choice of the number of simultaneous data streams. When several systems share the same spectrum, distributed adaptive channel allocation can be obtained based on individual utility functions. The equilibria of such schemes have been analyzed based on game theory. Modifications of the utility functions have been proposed to improve the overall spectrum utilization.
In the development and evaluation of transmission schemes, realistic channel models are crucial. In particular, we have studied the joint characteristics of the propagation to a receiver from several transmitters.
Statistical Signal Processing
Estimation of covariance matrices is often an integral part in many signal processing algorithms. In MIMO communications or in signal modeling of EEG data the covariance matrix can sometimes be modeled as the Kronecker product of two smaller covariance matrices. These smaller matrices may also be structured, e.g., being Toeplitz or at least persymmetric. Recently we proposed a closed form maximum likelihood (ML) based method for the estimation of the Kronecker factor matrices. We also extended the method to be able to impose the persymmetric constraint into the estimator. Numerical examples show an excellent performance even for very small sample sizes. The associated structural detection problem was also discussed.
Measuring and combating effects of dirty radio
The development of contemporary and future wireless communication systems puts high demands on accurate and time-efficient test methods for production and product validation. Efficient measurement methods are also a prerequisite for digital correction to combat impairments produced by the analog circuitry, including IQ-mixers, analog-digital converters, and power amplifiers. We are interested in studying the impact of the radio-frequency front-end impairments on the performance of contemporary and future wireless communication. Our work span from basic research to measurements on our USRP-based MIMO testbed.
Navigation Systems
In-car navigation has been a killer application for GPS receivers, and a variety of electronics for consumers and professionals have been launched on a large scale. Positioning technologies based on stand-alone GPS receivers are vulnerable and, thus, have to be supported by additional information sources to obtain the desired accuracy, integrity, availability, and continuity of service. It is possible to save many lives in future rescue operations by developing a robust personnel-positioning system with high accuracy and availability. Robust communication and positioning systems are eagerly awaited for by rescue personnel. These systems have the potential to increase their safety in many critical operation scenarios such as natural disasters, terrorist attacks, as well as for police and military users. Within the laboratory, we perform basic research in sensor fusion by a plurality of sensors (IMU, GPS, UWB-positioning, and cameras), time synchronization in loosely coupled navigation systems, to application-oriented work for advanced driver assistance systems to classification of railroad curvature.
