An Effective Quantization and Reconstruction Mechanism in IR-UWB Based on Compressed Sensing

The compressed sensing(ACS) theory has provided a new solution for the low-rate sampling design of Impulse Radio Ultra-WideBand (AIR-UWB) signal. This paper gives full consideration of the influence of quantization noise in IR-UWB system, and designs an effective quantization and reconstruction mechanism with high performance of resisting noise. Based on the analysis of noise distribution characteristics in compressed sampling value, the signal reconstruction model is revised, and then the performances of Dantzig-Selector (ADS) method, Subspace Pursuit(ASP) method, and traditional reconstruction algorithms are compared. On this basis, a signal reconstruction method (Ahybrid DS-SP method) with self-adaptability in DS and SP is proposed. Based on hybrid DS-SP method and consideration of overload uniform quantization, overload hybrid DS-SP mechanism is proposed which considered both the digital rear-end and analog front-end of IR-UWB receiver under compressed sensing framework. Simulation results show that the overload hybrid DS-SP mechanism achieves the exceptional reconstruction performance compared to the traditional reconstruction algorithms under different noise conditions with a compromised complexity between DS and SP.