Research Areas (Under Construction)

Communication Networks

With the realisation of new generations of network technologies, the integration and interoperation of multiple heterogeneous networks supporting mobile services and user facilities will be of great importance. Our team is concerned with research leading to the development of techniques to enhance the responsiveness of new technologies and systems when facing dynamic traffic changes, a variety of user requirements and the deployment of new services.

Mobile Communications

The highly successful introduction and rapid growth of mobile telephone networks has re-emphasised the need for the efficient use of the limited bandwidth that is available. The activity of the mobile communication research group is, in one way or another, concerned with the research into techniques for improving the efficiency of bandwidth utilisation, and with techniques for improving the reliability of communication over fading channels.

Sparse Signal Processing and Compressed Sensing

The notion of sparsity, namely the idea that the essential information contained in a signal can be represented with a small number of significant components, is widespread in signal processing and data analysis in general. Great progress for example in image compression and enhancement has been obtained by modeling signals as sparse in an appropriate domain, typically the wavelet domain. The understanding that sparsity can be used to drive directly the information acquisition process is instead much more recent.
The group has years of experience in sparse signal representation, sampling based on sparsity models and applications in sparse inference, compression, super-resolution and tracking. Current research projects are in the area of dictionary learning for sparse representation, construction of sampling matrices/operators, finite rate of innovation sampling and a wide range of applications from estimation of diffusion fields, to imaging and neuroscience as well as channel estimation and sensing.

Information Theory

Information theory has been instrumental in identifying the fundamental performance limits of communication systems, and more importantly, has guided the development of capacity-achieving coding and communication techniques. In recent years, the influence of information theory has grown beyond communications, the area that led to its initial development, and it has found novel applications in diverse research areas such as machine learning, privacy/ secrecy, bioinformatics, cloud and finance. Our group has extensive experience in multi-user information theory, information theoretic privacy and secrecy, source and channel coding, as well as information theoretic analysis of noisy databases.