In this paper, an analytical framework is presented for device detection in an impulse radio (IR) ultra-wide bandwidth (UWB) system and its performance analysis is carried out. The Neyman–Pearson (NP) criteria is employed for this device-free detection. Different from the frequency-based approaches, the proposed detection method utilizes time domain concepts. The characteristic function (CF) is utilized to measure the moments of the presence and absence of the device. Furthermore, this method is easily extendable to existing device-free and device-based techniques. This method can also be applied to different pulse-based UWB systems which use different modulation schemes compared to IR-UWB. In addition, the proposed method does not require training to measure or calibrate the system operating parameters. From the simulation results, it is observed that an optimal threshold can be chosen to improve the ROC for UWB system. It is shown that the probability of false alarm, $P_{FA}$, has an inverse relationship with the detection threshold and frame length. Particularly, to maintain $P_{FA}<{10}^{-5}$ for a frame length of 300 ns, it is required that the threshold should be greater than $2.2$. It is also shown that for a fix $P_{FA}$, the probability of detection $P_D$ increases with an increase in interference-to-noise ratio (INR). Furthermore, $P_D$ approaches 1 for INR $>-2$ dB even for a very low $P_{FA}$ i.e., $P_{FA}=1\times {10}^{-7}$. It is also shown that a 2 times increase in the interference energy results in a 3 dB improvement in INR for a fixed $P_{FA}=0.1$ and $P_D=0.5$. Finally, the derived performance expressions are corroborated through simulation.

中文翻译：

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脉冲无线电超宽带系统中的无设备检测


本文提出了一种用于脉冲无线电（IR）超宽带（UWB）系统中设备检测的分析框架，并对其进行了性能分析。内曼-皮尔逊 (NP) 标准用于这种无设备检测。与基于频率的方法不同，所提出的检测方法利用时域概念。特征函数（CF）用于测量设备存在和不存在的时刻。此外，该方法可以轻松扩展到现有的无设备和基于设备的技术。该方法还可应用于不同的基于脉冲的 UWB 系统，这些系统使用与 IR-UWB 不同的调制方案。此外，所提出的方法不需要训练来测量或校准系统操作参数。从仿真结果可以看出，可以选择最佳阈值来提高 UWB 系统的 ROC。结果表明，误报的概率，${磷}_{F\mathrm{一个}}$，与检测阈值和帧长度成反比关系。特别是要维持${磷}_{F\mathrm{一个}}<{10}^{-5}$对于300 ns的帧长度，要求阈值应大于。它还表明，对于修复${磷}_{F\mathrm{一个}}$, 检测概率${磷}_D$随着干扰噪声比 (INR) 的增加而增加。 此外，${磷}_D$ INR 接近 1$>-2$ dB 即使对于非常低的${磷}_{F\mathrm{一个}}$IE，${磷}_{F\mathrm{一个}}=1\times {10}^{-7}$ 。还表明，对于固定的干扰能量，干扰能量增加 2 倍会导致 INR 提高 3 dB。${磷}_{F\mathrm{一个}}=0.1$和${磷}_D=0.5$ 。最后，通过仿真验证了推导的性能表达式。