Compressed Sensing in Wireless Communication

This is a poster from the Workshop on Sparsity, Localisation and Dictionary Learning in London, 2012.

In our research group at Aalborg University we are using compressed sensing theory to address some important practical challenges in radio frequency communication and more generally in analog-to-digital conversion.
Radio frequency receivers for modern  telecommunication standards in power-constrained devices are increasingly challenged by the necessary sampling frequencies and hardware power consumption. Compressed sensing techniques may help address some of these challenges, for example by reducing the necessary sampling rate. This is a move towards the original, but hardware-wise unrealistic, ideas of software defined radios.
In order to utilise compressed sensing, we must be able to represent the relevant signals sparsely – or, alternatively, find new signal structures that allow compressed sensing.
In practice, various hardware imperfections as well as noise and interference limit the applicability of compressed sensing. These issues must be addressed to make compressed sensing practicable.