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On interference detection using higher-order statistics

机译:关于使用高阶统计量的干扰检测

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In applications with strict requirements regarding reliability and real time capability such as factory and process automation, it is critical to detect sources of interference that might corrupt data packets leading to retransmissions and delays. To tackle this issue we propose a method for measuring and quantifying radio interference using higher-order statistics. Unlike traditional energy detectors that suffer from several shortcomings in noisy environments, higher-order statistics are robust and do not suffer from threshold uncertainties. We present results of experimental measurements as well as simulations for detecting mutual interference using a normalized fourth-order moment named the kurtosis. The proposed method is independent of the received power and is efficient for detecting low-level interference compared to energy detectors. Results show that not only the presence of interference could be detected but also its strength. As a use case, the proposed method has been applied to Bluetooth mutual interference in this work. In can however be extended to other standards and scenarios.
机译:在对可靠性和实时性有严格要求的应用中,例如工厂和过程自动化,检测可能破坏数据包导致重传和延迟的干扰源至关重要。为了解决这个问题,我们提出了一种使用高阶统计量来测量和量化无线电干扰的方法。与传统的能量检测器在嘈杂的环境中会遇到一些缺点不同,高阶统计量是可靠的,并且不会受到阈值不确定性的影响。我们介绍了实验测量的结果,以及使用称为峰度的归一化四阶矩检测相互干扰的模拟。所提出的方法与接收功率无关,并且与能量检测器相比,对于检测低电平干扰是有效的。结果表明,不仅可以检测到干扰的存在,而且可以检测到干扰的强度。作为一种使用案例,在这项工作中,所提出的方法已应用于蓝牙相互干扰。但是,可以扩展到其他标准和方案。

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