基于压缩感知的超宽带通信信号处理与检测机制研究

项目名称： 基于压缩感知的超宽带通信信号处理与检测机制研究

项目编号： No.61471222

项目类型： 面上项目

立项/批准年度： 2015

项目学科： 无线电电子学、电信技术

项目作者： 王德强

作者单位： 山东大学

项目金额： 76万元

中文摘要： A/D转换是制约超宽带通信技术发展的技术瓶颈。本项目基于软件无线电理念，利用新兴的压缩感知理论实现超宽带信号低速率采样，并试图在压缩数字域实现超宽带接收机的信号处理与检测功能。首先，从超宽带多径信号统计特征入手，利用主分量分析、独立分量分析研究超宽带信号稀疏表示方法，构建统计意义下最优的稀疏基字典，降低观测电路实现复杂度和重构算法复杂度；基于匹配滤波思想研究预处理矩阵设计方法，构建信号能量捕获效率高、噪声抑制能力强的复合观测矩阵。然后，基于压缩感知序列，研究压缩数字域信号处理与检测机制，提出高效的训练序列辅助的同步捕获算法和窄带干扰检测与抑制算法，探讨观测子空间检测和信号子空间检测两种符号检测机制，针对两种检测机制分别提出可行的信道估计算法、分集合并算法和符号检测算法。本项目的研究将适应物联网发展的迫切需求，并可为未来宽带无线通信技术发展提供新思路和理论依据。

中文关键词： 超宽带通信；接收机；压缩感知；信号处理；符号检测

英文摘要： Analog-to-digital conversion is the bottleneck hampering the development of ultra-wideband communications. Based on the concept of software-defined radio (SDR), the proposed research utilizes the emerging compressed sensing theory to lower the sampling rate of ultra-wideband signals and attempts to realize the signal processing functions and symbol detection of ultra-wideband receivers in compressed digital domain. Firstly, starting from the statistics of ultra-wideband multipath signals and utilizing principal component analysis (PCA) and/or independent component analysis (ICA), we will investigate the sparse decomposition of ultra-wideband signals and construct statistically optimal dictionary of sparse bases such that both the measurement circuitry complexity and the reconstruction algorithm complexity can be reduced effectively. Based on the idea of matched-filtering, we will investigate the design methodology of preprocessing matrix based on which compound measurement matrices with efficient signal energy capture and ability of noise suppression can be constructed. After that, based on the measurement sequences obtained, we will investigate the signal processing and symbol detection mechanism. Efficient training sequence-assisted synchronization algorithm will be established and algorithm for narrowband interference detection and suppression will be proposed also. Two symbol detection mechanisms, named measurement subspace detection and signal subspace detection, will be studied. For each symbol detection mechanism, channel estimation algorithm, diversity combining algorithm and symbol detection algorithm will be proposed. This research will meet the urgent needs of the development of internet of things (IOT) and also provide new ideas and theoretical fundamentals to the future wideband wireless communications.

英文关键词： Ultra-wideband Communication;Receiver;Compressed Sensing;Signal Processing;Symbol Detection