【作者】 李健；

【导师】 王德强；

【作者基本信息】 山东大学 ， 信息与通信工程， 2018， 硕士

【摘要】 超宽带是短距离无线通信领域的研究热点之一,信道估计是超宽带接收机设计不可或缺的组成部分。由于超宽带信号带宽极宽,根据奈奎斯特采样定理,数字接收机需要以极高的速率进行采样,这对于超宽带接收机的低成本、低功耗实现是个极大的挑战。近年来,压缩感知理论被应用于超宽带系统,为超宽带信号的低速率采样提供了可行的解决思路。然而,大维度信号的压缩感知和重构在实现复杂度方面仍面临着诸多问题。本文研究分段压缩感知及其在超宽带信道估计中的应用。主要研究成果包括以下三个方面:1.对于给定的信号模型,提出压缩感知重构成功率下界的计算公式,结合分段压缩感知特点,将重构成功率下界推广到分段压缩感知的情景。结合等角紧框架、Welch界、OMP算法重构能力等先验知识,可以确定观测矩阵的最大重构能力。对于给定的信号模型,将重构能力范围内的所有信号图案被取到的概率进行累加,得到重构成功率下界计算公式。重构成功率下界对于压缩感知与重构的性能评估具有指导性意义。仿真结果充分验证了重构成功率下界计算公式的合理性。2.为进一步提升分段压缩感知重构性能,提出分段压缩感知改进方案。在分段压缩感知重构成功率下界计算公式的指导下,适配不同信号段之间的差异性,为各个信号段设计不同重构能力的观测矩阵。在分段压缩感知观测值数量均匀分配的基础上,我们提出了根据比例因子进行观测值非均匀分配的改进方案,比例因子可根据各段信号的能量来确定。仿真结果表明,该方案优于传统分段压缩感知方案,并同时优于不分段的压缩感知方案。3.针对超宽带信道能量分布统计特征,提出分段压缩感知超宽带信道估计改进方案。该方案利用超宽带信道的平均功率延迟剖面这一先验知识,统计得出观测值分配因子,实现信道估计过程中观测值的非均匀分配。仿真结果表明:当观测值数量相同时,改进方案相较于原来的分段压缩感知超宽带信道估计方案和整体信道估计方案有更好的信道估计精度和更优秀的误码率性能。更多还原

【Abstract】 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.更多还原