Compressed Sensing soft activity processing for sparse multi-user systems

Performing joint activity and data detection has recently gained ubiquitous attention for reducing signaling overhead in multi-user Machine-to-Machine Communication systems. To this end investigations on the application of Compressed Sensing have focused on estimating data and node activity jointly in scenarios where the per node activity is very low. The focus of this paper is to enhance the performance of state of the art detectors by the utilization of soft information. In particular we provide a formulation of activity Log-Likelihood ratios, that we utilize to improve the activity detection.