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首页> 外文期刊>Expert Systems with Application >The performance evaluation of a spectrum sensing implementation using an automatic modulation classification detection method with a Universal Software Radio Peripheral
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The performance evaluation of a spectrum sensing implementation using an automatic modulation classification detection method with a Universal Software Radio Peripheral

机译：使用自动调制分类检测方法和通用软件无线电外围设备进行频谱感测实现的性能评估

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摘要

Based on the inherent capability of automatic modulation classification (AMC), a new spectrum sensing method is proposed in this paper that can detect all forms of primary users' signals in a cognitive radio environment. The study presented in this paper focuses on the sensing of some combined analog and digitally primary modulated signals. In achieving this objective, a combined analog and digital automatic modulation classifier was developed using an artificial neural network (ANN). The ANN classifier was combined with a GNU Radio and Universal Software Radio Peripheral version 2 (USRP2) to develop the Cognitive Radio Engine (CRE) for detecting primary users' signals in a cognitive radio environment. The detailed information on the development and performance of the CRE are presented in this paper. The performance evaluation of the developed CRE shows that the engine can reliably detect all the primary modulated signals considered. Comparative performance evaluation carried out on the detection method presented in this paper shows that the proposed detection method performs favorably against the energy detection method currently acclaimed the best detection method. The study results reveal that a single detection method that can reliably detect all forms of primary radio signals in a cognitive radio environment, can only be developed if a feature common to all radio signals is used in its development rather than using features that are peculiar to certain signal types only.
机译：基于自动调制分类（AMC）的固有能力，本文提出了一种新的频谱感知方法，该方法可以在认知无线电环境中检测各种形式的主要用户信号。本文提出的研究重点是对一些组合的模拟和数字原始调制信号的感测。为了实现这一目标，使用人工神经网络（ANN）开发了组合的模拟和数字自动调制分类器。 ANN分类器与GNU Radio和通用软件Radio Peripheral版本2（USRP2）结合在一起，开发了认知无线电引擎（CRE），用于在认知无线电环境中检测主要用户的信号。本文介绍了CRE的开发和性能的详细信息。对已开发的CRE的性能评估表明，发动机可以可靠地检测出所考虑的所有主要调制信号。对本文提出的检测方法进行的性能比较评估表明，与目前被誉为最佳检测方法的能量检测方法相比，该方法具有良好的性能。研究结果表明，只有在开发中使用了所有无线电信号共有的特征而不是使用特定于特征的特征时，才能开发出能够可靠地检测认知无线电环境中所有形式的一次无线电信号的单一检测方法。仅某些信号类型。

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