基于压缩感知的通信信号处理理论研究

项目名称： 基于压缩感知的通信信号处理理论研究

项目编号： No.U1530154

项目类型： 联合基金项目

立项/批准年度： 2016

项目学科： 数理科学和化学

项目作者： 方俊

作者单位： 电子科技大学

项目金额： 63万元

中文摘要： 本项目针对大带宽、多信号、多调制样式的复杂通信信号处理面临的奈奎斯特采样和信号特征提取等关键技术问题，开展基于压缩感知的通信信号处理理论研究。具体的来说，研究通信信号的稀疏表征，设计有效的字典学习算法，寻求通信信号或其特征量的稀疏表征基；研究压缩信号处理理论与算法，利用压缩数据完成对通信信号的检测、定阶、和调制识别等问题，克服奈奎斯特采样瓶颈问题；针对宽带通信信号的结构稀疏特性，研究新型高精度、低复杂度稀疏重构算法，满足宽带信号重构的实时性和高精度要求；研究基于一比特压缩感知和压缩信号处理方法，降低硬件设计复杂度，减少采样数据量，更高效的完成数据分析和处理。本项目的研究，有助于压缩感知方法的完善，促进解决大宽带复杂通信信号处理的瓶颈技术问题，促进无线通信和军事监测事业的发展。

中文关键词： 压缩感知；压缩信号处理；次奈奎斯特采样；调制识别

英文摘要： The purpose of this research project is to explore new compressed sensing theories and techniques for sub-Nyquist sampling and analysis of complex wideband communication signals. Our research consists of the following four aspects. Firstly, we aim to seek a basis on which the complex wideband communication signal or its higher-order statistics has a sparse or approximate sparse representation. Secondly, we develop new compressed signal processing theories and techniques to accomplish the detection, estimation, and modulation recognition of wideband communication signals based solely on the down-sampled measurements, which can help overcome the difficulty of Nyquist sampling of wideband signals. Thirdly, by exploiting the block-sparse structure of wideband communication signals, we develop sparse signal recovery algorithms which have very low computational complexity but meanwhile can still provide state-of-the-art recovery performance. Lastly, one-bit compressed sensing techniques are developed to dramatically reduce the hardware complexity. The ultimate goal of this research is to overcome the deficiencies in existing compressed sensing techniques, and develop efficient compressed sensing methods for sub-Nyquist sampling and analysis (such as estimation and modulation recognition) of complex wideband communication signals.

英文关键词： Compressed sensing;Compressed signal processing;Sub-Nyquist sampling;modulation recognition