Cognitive Radios Exploiting Gray Spaces via Compressed Sensing
Cognitive Radios Exploiting Gray Spaces via Compressed Sensing
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DOI：
10.1515/freq-2015-0145
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发表时间：
2016
期刊：
影响因子：
1.1
通讯作者：
Dennis Wieruch;P. Jung;T. Wirth;A. Dekorsy;T. Haustein
中科院分区：
文献类型：
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作者：
Dennis Wieruch;P. Jung;T. Wirth;A. Dekorsy;T. Haustein
摘要我们提出了一种交织的认知无线电系统与灰色空间检测器，这是正确地识别一个主用户系统，如3GPP LTE的活动频带内的一小部分未使用的资源。因此，灰色空间检测器可以科普频率衰落空洞，并将它们与非活动资源区分开。研究了灰度空间检测器的不同方法，传统的降秩最小二乘法以及基于压缩感知的正交匹配追踪和基追踪去噪算法。此外，还将灰度空间检测器与经典能量检测器进行了比较。仿真结果给出了接收机在几个SNR下的工作特性，以及实际虚警率下基站系统负载等方面的检测性能。结果表明，特别是对于实际的虚警率，压缩感知算法比经典的能量检测器和降秩最小二乘法更适合。
Abstract We suggest an interweave cognitive radio system with a gray space detector, which is properly identifying a small fraction of unused resources within an active band of a primary user system like 3GPP LTE. Therefore, the gray space detector can cope with frequency fading holes and distinguish them from inactive resources. Different approaches of the gray space detector are investigated, the conventional reduced–rank least squares method as well as the compressed sensing–based orthogonal matching pursuit and basis pursuit denoising algorithm. In addition, the gray space detector is compared with the classical energy detector. Simulation results present the receiver operating characteristic at several SNRs and the detection performance over further aspects like base station system load for practical false alarm rates. The results show, that especially for practical false alarm rates the compressed sensing algorithm are more suitable than the classical energy detector and reduced–rank least squares approach.