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.

中文翻译：

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环境对无线传感器网络中基于硬件的链路质量估算器的影响。

无线传感器网络中基于硬件的链路质量估计器（LQE）通常使用物理层参数来估计分组接收率，这具有高敏捷性和低开销的优点。但是，许多现有研究并未考虑环境变化对这些估计量的适用性的影响。本文比较了典型的基于硬件的LQE在不同环境中的性能。同时，针对现有研究中存在问题的信噪比（SNR）计算方法，提出了一种更为合理的计算方法。结果表明，使用通信距离来估计分组接收速率是不准确的，并且当环境改变时可能是无用的。同时，接收信号强度指示器的波动范围（RSSI和SNR都会受到影响，而链路质量指标（LQI）几乎没有变化。当环境变化时，基于RSSI的LQE的性能可能会降低。幸运的是，这种降级主要是由背景噪声的变化引起的，可以方便地进行补偿。通过基于LQI和SNR的LQE，可以获得最佳的环境适应性，因为当环境变化时，它们几乎不受影响。此外，在过渡区域中，基于LQI的LQE比基于SNR的LQE更准确。不过，与SNR相比，LQI的波动范围要大得多，需要较大的平滑窗口才能收敛。另外，LQI的计算通常是特定于供应商的。因此，在实践中应考虑准确性，敏捷性和便利性之间的权衡。