Signal processing for communication

Contact: Geert Leus

Signal processing for communications is an important area within signal processing, as it covers around 20% of research. Among many questions, an important one is, how can multiple overlapping signals be separated? This problem is very relevant in wireless communications, where signals are overlapping in time, space and frequency (the 'cocktail party problem'). With multiple antennas and advanced separation techniques, the capacity and robustness of wireless links can greatly be improved. Similar problems are relevant in radio astronomy, where the sky signals of interest are contaminated by man-made interference (e.g., communication signals), which need to be estimated and suppressed. The resulting algorithms are formulated in terms of linear algebra operations and provide interesting test cases for embedded system design.

Array signal processing refers both to parallel signal processing of an array of signals as it occurs in a multiple antennas/receivers situation, and to the mapping of such algorithms onto parallel hardware platforms. This topic has great relevance in a number of contexts: the mobile communication context, separation of airplane transponder signals using phased antenna arrays, and spatial filtering for radio telescope arrays.

Topics studied can be classified under "techniques" and "applications".

Techniques

• Estimation and detection theory; statistical signal processing
• Array calibration and beamforming algorithms; source localization
• Performance analysis and bounds
• Distributed processing; optimization techniques
• Sampling and reconstruction theory
• Adaptive signal processing
• Space-time coding; modulation; acquisition, synchronization, tracking

Applications

• CDMA and spread spectrum; multicarrier and OFDM; UWB
• Sensor networks
• MIMO communication; wireless networks
• Radar and sonar signal processing; radio astronomy; geophysics; remote sensing

Research

In our work, we combine "techniques" with "applications". We work on a variety of applications, such as sensor networks for the process industry, a distributed radio telescope in space, an underwater communication system. Typically, there is a receiver (antenna array) which receives a collection of transmitted signals, perturbed by a multipath channel that may even be highly time-varying. The challenge then is to derive algorithms that estimate the channel and detect the transmitted data. Our work is theoretical: the development of new algorithms and the derivation of their performance, as well as practical: the development of experimental phased array measurement systems and the verification of the algorithms on the obtained data.

The focus of our work is as follows:

• Smart antenna technology for wireless communications: This includes research on algorithms for source separation, equalization and parameter estimation of communication signals, and application of blind source separation/equalization techniques to W-CDMA and OFDM.
• Signal processing over time-varying channels: If the transmitter and/or receiver is moving fast, a large Doppler spread makes the communication channel time-varying. This occurs in DVB-T systems (e.g., digital television received in high-speed trains), but is even more pronounced in acoustic underwater communication channels. The challenge is to estimate and compensate for these effects, especially for wideband (OFDM) signals.
• Signal processing for radio astronomy: The trend in radio astronomy is to construct large arrays of small antennas. An example is the LOFAR system, where 13,000 antennas are distributed over 100 stations in The Netherlands and Germany. In the future, we will have SKA (square kilometer array, consisting of 1 million antennas) and OLFAR, a distributed radio telescope in space. Central issues for us are array calibration, interference cancellation, and image formation using array processing techniques.

In the list below, you can see some of our related projects. Also check out the IEEE SPS DEGAS webinar series on graph signal processing which we coordinate.

Projects under this theme

History