A Compressed Sensing Approach for IR-UWB Communication

The emerging theory of compressed sensing (CS) not only enables the reconstruction of sparse signals from a small set of random measurements, but also provides a universal signal demodulation approach at sub-Nyquist sampling rate. Compressed signal demodulation is particularly suitable for impulse ratio ultra-wideband (IR-UWB) communications where Nyquist sampling is a formidable challenge. In this paper, aiming at the signaling scheme that the pilot symbols are to provide side information about the channels and data symbols adopt BPM and M-PPM joint modulation, to realize 100Mbps UWB communication system under compressed sensing framework. We introduce the correlation matrix for UWB channel estimation, and propose two compressed demodulation methods: reconstruction mapping (RM) method and compressed signal classification (CSC). Simulation results show that the introduction of correlation matrix, improves channel estimation performance. The two demodulation methods also have a good performance in simulation, and provide a new idea for UWB signal demodulation.