Analysis on data compression of two-stage sensing for cognitive radio
Analysis on data compression of two-stage sensing for cognitive radio
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DOI：
10.1109/cspa.2018.8368691
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发表时间：
2018-03
期刊：
影响因子：
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通讯作者：
Hiroki Kobayashi;H. Ichikawa;Yuusuke Kawakita
中科院分区：
文献类型：
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作者：
Hiroki Kobayashi;H. Ichikawa;Yuusuke Kawakita
在使用认知无线电的无线网络系统中，通过协作感知和宽带感知收集大量的感知数据。在这样的系统中，需要高分辨率的传感数据，用于高信号检测精度，以保护主用户和分析接收到的信号。为了实现传感数据的压缩和高分辨率，提出了两级传感：基于亚奈奎斯特的宽带数据压缩传感和高分辨率窄带传感。在本文中，我们提出了一个分析的数据压缩的两级传感。针对基于亚奈奎斯特的宽带感知的压缩结构和重构算法，提出了几种方法。然而，由于方法的差异而导致的压缩性能尚未进行比较。通过改变信号稀疏度和信道位置，对随机解调器、随机滤波器和调制宽带转换器三种压缩结构以及基追踪和正交匹配追踪两种重构算法的整个两级感知过程的压缩性能进行了评估。结果产生了具有良好压缩性能的方法组合。
In wireless network systems that use cognitive radio, massive amounts of sensing data are collected by cooperative sensing and wideband sensing. In such a system requires high resolution sensing data for high signal detection accuracy to protect the primary users and analysis of the received signals. In order to achieve compressing sensing data and high resolution, two-stage sensing: sub-Nyquist-based wideband sensing with data compression and high-resolution narrowband sensing has been considerd. In this paper, we present an analysis on the data compression of two-stage sensing. Several methods have been proposed for the compressive architecture and reconstruction algorithm of sub-Nyquist-based wideband sensing. However, compression performance due to differences in methods has not been compared. We evaluated the compression performance of the whole two-stage sensing process for three compressive architectures that are Ramdom Demodulator, Rondom Filtering and Modulated Wideband Converter and two reconstruction algorithms that are Basis Pursuit and Orthogonal Matching Pursuit by changing the signal sparsity and channel placement. The results yielded a combination of methods with good compression performance.