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Environmental Impacts on Hardware-Based Link Quality Estimators in Wireless Sensor Networks

机译:无线传感器网络中基于硬件的链路质量估计的环境影响

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摘要

Hardware-based link quality estimators (LQEs) in wireless sensor networks generally use physical layer parameters to estimate packet reception ratio, which has advantages of high agility and low overhead. However, many existing studies didn’t consider the impacts of environmental changes on the applicability of these estimators. This paper compares the performance of typical hardware-based LQEs in different environments. Meanwhile, aiming at the problematic Signal-to-Noise Ratio (SNR) calculation used in existing studies, a more reasonable calculation method is proposed. The results show that it is not accurate to estimate the packet reception rate using the communication distance, and it may be useless when the environment changes. Meanwhile, the fluctuation range of the Received Signal Strength Indicator (RSSI) and SNR will be affected and that of Link Quality Indicator (LQI) is almost unchanged. The performance of RSSI based LQEs may degrade when the environment changes. Fortunately, this degradation is mainly caused by the change of background noise, which could be compensated conveniently. The best environmental adaptability is gained by LQI and SNR based LQEs, as they are almost unaffected when the environment changes. Moreover, LQI based LQEs are more accurate than SNR based ones in the transitional region. Nevertheless, compared with SNR, the fluctuation range of LQI is much larger, which needs a larger smoothing window to converge. In addition, the calculation of LQI is typically vendor-specific. Therefore, the tradeoff between accuracy, agility, and convenience should be considered in practice.
机译:无线传感器网络中基于硬件的链路质量估计(LQE)通常使用物理层参数来估计分组接收比,这具有高敏捷性和低开销的优点。然而,许多现有的研究没有考虑对这些估算者的适用性的环境变化的影响。本文比较了不同环境中典型的硬件基于LQE的性能。同时,针对现有研究中使用的有问题的信噪比(SNR)计算,提出了一种更合理的计算方法。结果表明,使用通信距离估计分组接收速率是不准确的,并且在环境变化时可能是无用的。同时,接收信号强度指示器(RSSI)和SNR的波动范围将受到影响,并且链路质量指示符(LQI)几乎不变。基于RSSI的LQE的性能可能在环境变化时降低。幸运的是,这种降级主要是由背景噪声的变化引起的,这可以方便地得到补偿。 LQI和SNR基LQE获得了最佳的环境适应性,因为当环境变化时,它们几乎不受影响。此外,基于LQI的LQE在过渡区域中的SNR基于SNR的LQE更加精确。然而,与SNR相比,LQI的波动范围大得多,需要更大的平滑窗口来汇聚。此外,LQI的计算通常是特定于供应商的。因此,应在实践中考虑准确性,敏捷性和便利性之间的权衡。

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