Compressed Sensing Based UWB Receiver Using Signal-Matched Sparse Measurement Matrix

Abstract

In this paper, we propose a deterministic signal-matched sparse measurement matrix for ultra wideband (UWB) systems. The proposed matrix is easy to implement and is computationally efficient as needed in a practical system. The proposed matrix captures higher signal energy in the compressive sensing (CS) domain as compared to the commonly used random matrices. Furthermore, a simple OneShot signal recovery of a full (Nyquist rate) signal from its sub-Nyquist rate measurement samples is proposed for symbol detection. Theoretical analysis and simulation results demonstrate that the detection performance of a CS-based UWB receiver using the proposed matrix is better than the random measurement matrices and is close to a conventional system sampled at full Nyquist rate.