Sparse Signal Processing in Wireless Communications (SparSig)

This project proposes a new way to sample, quantize, process and re-synthesize analog signals. Generally, the signals in many scientific areas are sparse in nature, which means that there is some structure and redundancy in the signals. If it is possible to transform a signal into a sparse domain in such a way that only the really needed information is processed then it is possible to save energy.



This project focuses on wireless communication and signals for such a system - specifically: 1) in a communication receiver where a radio frequency signal must be sampled (down-converted) and processed, and 2) to process real audio and video baseband signals.



The main contributions are to develop a framework for handling realistic signals (which are noisy, distorted etc.) and to provide a convincing validation (including experiments) of the achieved results. It is the objective to reduce the power consumption of current state-of-the-art techniques for converters and digital signal processing by at least 50% in the devices typically used in wireless communication systems.



The team is composed of two sections from Aalborg University (applied signal processing and RF signal techniques), one department from Lund University, Sweden (converters in integrated circuit design), and KU Leuven, Belgium (fundamental signal processing), as well as two industrial companies (Texas Instruments, Dallas, USA and Innovative RF which is a Danish start-up). In total four professors are involved in the project together with 3 PhD students and 2 postdocs in an international setting.