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An Improved Spectrum Sensing Method Based on Multitaper-Singular ValueDecomposition in Cognitive Radio

机译:一种改进的基于认知收音机多销 - 奇异ValudeComposith的频谱传感方法

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In order to improve the spectrum hole detection in Cognitive radio (CR), Multitaper Method with Singular Value Decomposition (MTM-SVD) has been proposed. However, how to decide the coefficient in the spatiotemporal complex matrix constructed by MTM-SVD is still under discussion. In this paper, a new scheme, employing array signal processing, for coefficient determination is introduced. Since the sensor used in spectrum sensing is attached with antenna array, the directions of the interference sources can be computed by Multiple Signal Classification (MUSIC) algorithm. By using multiple sensors, the position of the interference source can be estimated. Moreover, the coefficient in MTM-SVD is related to the distance between the sensor and the interference source. Therefore, a more proper value of the coefficient will be given and the interference temperature will be estimated more accurately. Simulation results show that, the proposed method has a better performance for spectrum hole detection than the conventional method.
机译:为了改善认知无线电(CR)中的频谱空穴检测,提出了具有奇异值分解(MTM-SVD)的多件方法。然而,如何在MTM-SVD构建的时空复合矩阵中确定系数仍在讨论。本文介绍了采用阵列信号处理的新方案,用于系数确定。由于在光谱感测中使用的传感器附加有天线阵列,因此可以通过多个信号分类(音乐)算法来计算干扰源的方向。通过使用多个传感器,可以估计干扰源的位置。此外,MTM-SVD中的系数与传感器和干扰源之间的距离有关。因此,将给出更适当的系数值,并且将更精确地估计干扰温度。仿真结果表明,该方法具有比传统方法更好的频谱空穴检测性能。

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