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Compressive Measurement of Spread Spectrum Signals

机译:扩频信号的压缩测量

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摘要

Spread Spectrum (SS) techniques are methods used in communication systems where the spectra of the signal is spread over a much wider bandwidth. The large bandwidth of the resulting signals make SS signals difficult to intercept using conventional methods based on Nyquist sampling. Recently, a novel concept called compressive sensing has emerged. Compressive sensing theory suggests that a signal can be reconstructed from much fewer measurements than suggested by the Shannon Nyquist theorem, provided that the signal can be sparsely represented in a dictionary. In this work, motivated by this concept, we study compressive approaches to detect and decode SS signals. We propose compressive detection and decoding systems based both on random measurements (which have been the main focus of the CS literature) as well as designed measurement kernels that exploit prior knowledge of the SS signal. Compressive sensing methods for both Frequency-Hopping Spread Spectrum (FHSS) and Direct Sequence Spread Spectrum (DSSS) systems are proposed.
机译:扩频(SS)技术是在通信系统中使用的方法,其中信号的频谱在更宽的带宽上扩展。结果信号的大带宽使SS信号难以使用基于Nyquist采样的常规方法进行拦截。近来,出现了称为压缩感测的新颖概念。压缩感测理论表明,只要可以在字典中稀疏表示信号,就可以用比Shannon Nyquist定理所建议的少得多的测量值来重构信号。在这项工作的启发下,我们以这种概念为基础,研究了压缩方法来检测和解码SS信号。我们提出了基于随机测量(这是CS文献的主要焦点)以及利用SS信号先验知识的设计测量内核的压缩检测和解码系统。提出了针对跳频扩频(FHSS)和直接序列扩频(DSSS)系统的压缩感测方法。

著录项

  • 作者

    Liu Feng;

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  • 年度 2015
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  • 原文格式 PDF
  • 正文语种 en_US
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