Signal Recovery by Compressed Sensing in IR-UWB Systems

In Impulse radio Ultra-Wideband (IRUWB) system, extremely high sampling rate is required for digital processing, it is difficult to meet this requirement under the current level of the hardware chips. Considering of the time-domain sparsity of IR-UWB communication signals, a novel signal recovery method is proposed to reduce the sampling rate based on Compressed sensing (CS) theory. The CS reconstruction model is developed, where the entries of quasi-Toeplitz measurement matrices satisfy with the logarithm normal distribution, and the feasibility of recovering the IR-UWB communication signals is proved by Restricted isometry property (RIP) analyzing. Simulation experiments are performed with Orthogonal matching pursuit (OMP) algorithm, and the results demonstrate that 1/10–1/20 of the Nyquist sampling rate will be sufficient to efficiently recover the IR-UWB communication signals.