Compressive sensing and waveform design for the identification of Linear time-varying systems

In this paper, we investigate the application of compressive sensing and waveform design for estimating linear time-varying system characteristics. Based on the fact that the spreading function system representation is sparse in realistic system scenarios, we propose a new method for the identification of narrowband, wideband and dispersive systems using a small set of measurements. Through numerical simulations, we successfully demonstrate the feasibility of using compressive sensing to estimate the system spreading function.