A joint sparse signal reconstruction and channel estimation for UWB communication system

Ultra-wideband(UWB) radio has gained a major breakthrough in wireless communications. However, the sampling is a huge obstacle to it. Applying compressed sensing(CS) principle which can recover a sparse signal from less measurement to UWB communication has been a hot topic for many years. This paper shows two methods to construct the CS model for UWB communication, jointing the signal reconstruction and channel estimation together using the CS approach, one takes a suitable sensing matrix to process the received signal and the other exploits the channel itself as a sensing process. A comparison is made at last between the CS based method and the traditional one. The simulation results demonstrate that our jointing CS method can achieve better performance at low SNR and high bit rate.