Compressed Sensing Of UWB Signals Based On Divide-and-Conquer

UWB is one of the hot topics in the field of short range wireless communication.Channel estimation is an integral part of the design of UWB receivers.Because the bandwidth of UWB signal is very wide,according to Nyquist sampling theorem,digital receivers need to sample at very high rate,which is a great challenge for ultra wideband receivers to achieve low cost and low power consumption.In recent years,the theory of compressed sensing has been applied to UWB systems,which provides a feasible solution for the low rate sampling of UWB signals.However,the compression perception and reconstruction of large dimension signals still face many problems in terms of realization complexity.In this paper,segmented compressed sensing and its application in UWB estimation are studied.The main research results include the following three aspects:1.For a given signal model,a formula for the lower bound of the reconstruction success rate of compressed sensing is proposed.Combined with the characteristics of segmented compressed sensing,the lower bound of the reconstruction success rate is generalized to the scene of segmented compressed sensing.Combining the prior knowledge of the equiangular tight frames,Welch bounds and OMP algorithm,we can determine the maximum reconstruction ability of the measurement matrix.For a given signal model,we accumulate the probability of all the signal patterns in the range of reconstruction capability,and get the formula of the lower bound of the reconstruction success rate.The lower boundary of reconstruction success rate is of guiding significance for performance evaluation of compressed sensing and reconstruction.The simulation results fully verify the reasonableness of the proposed lower bound calculation formula for the success rate of reconstruction.2.In order to further improve the performance of segmented compressed sensing,a segmented compressed sensing improvement scheme is proposed.Under the guidance of the formula of the lower bound of the reconstruction success rate of SCS,the proposed adapts the difference between different segments,and designs the measurements of segmented compressed sensing.We propose an improved scheme based on scale factor for non-uniform assignment of measurements.The scale factor can be determined based on the energy of each segment of the signal.The simulation results show that the proposed scheme is superior to the traditional segmented compressed sensing scheme and the non segmented compressed sensing scheme.3.In view of the statistical characteristics of UWB channel energy distribution,an improved scheme for SCS-based UWB channel estimation is proposed.The scheme uses the prior knowledge of the average power delay profile of the UWB channel,and obtains the assignment factor of the number of measurement statistically,so as to achieve the non-uniform assignment of measurements in the process of channel estimation.The simulation results show that,when the number of measurement is the same,the improved scheme gets better channel estimation accuracy and better bit error rate performance than the original SCS-based UWB channel estimation scheme and the overall channel estimation scheme.